In [1]:
import os
import scipy
from scipy import signal
import numpy as np
import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import pickle
from collections import deque
import glob
import imageio
imageio.plugins.ffmpeg.download()

from moviepy.editor import VideoFileClip
from IPython.display import HTML
%matplotlib inline

out_dir='./output_images/camera_calib/'
In [2]:
# prepare object points
nx = 9 #TODO: enter the number of inside corners in x
ny = 6 #TODO: enter the number of inside corners in y

# Arrays to store object points and image points from all the images.
objpoints = [] # 3d points in real world space
imgpoints = [] # 2d points in image plane.

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((ny*nx,3), np.float32)
objp[:,:2] = np.mgrid[0:nx, 0:ny].T.reshape(-1,2)

plt.figure(figsize=(12,30))

notfindimg = cv2.imread('./output_images/cannot_find_corner.png')

for i in range(20):
    plt.subplot(10,2,i+1)
    
    fname = './camera_cal/calibration'+str(i+1)+'.jpg'
    print(fname)
    img = cv2.imread(fname)
    
    # Convert to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    # Find the chessboard corners
    ret, corners = cv2.findChessboardCorners(gray, (nx, ny), None)
    
     # If found, add object points, image points
    savefname = 'corners_found'+str(i+1)+'.jpg'
    
    if ret == True:
        objpoints.append(objp)
        imgpoints.append(corners)

        # Draw and display the corners
        cv2.drawChessboardCorners(img, (nx,ny), corners, ret)
                
        write_name = out_dir+savefname
        cv2.imwrite(write_name, img)
        print(write_name)
        plt.title(savefname,fontsize=10)
        plt.axis('off')
        plt.imshow(img)
    else:
        print('cannot find corner..')
        plt.title(savefname,fontsize=10)
        plt.axis('off')
        plt.imshow(notfindimg)
    
./camera_cal/calibration1.jpg
cannot find corner..
./camera_cal/calibration2.jpg
./output_images/camera_calib/corners_found2.jpg
./camera_cal/calibration3.jpg
./output_images/camera_calib/corners_found3.jpg
./camera_cal/calibration4.jpg
cannot find corner..
./camera_cal/calibration5.jpg
cannot find corner..
./camera_cal/calibration6.jpg
./output_images/camera_calib/corners_found6.jpg
./camera_cal/calibration7.jpg
./output_images/camera_calib/corners_found7.jpg
./camera_cal/calibration8.jpg
./output_images/camera_calib/corners_found8.jpg
./camera_cal/calibration9.jpg
./output_images/camera_calib/corners_found9.jpg
./camera_cal/calibration10.jpg
./output_images/camera_calib/corners_found10.jpg
./camera_cal/calibration11.jpg
./output_images/camera_calib/corners_found11.jpg
./camera_cal/calibration12.jpg
./output_images/camera_calib/corners_found12.jpg
./camera_cal/calibration13.jpg
./output_images/camera_calib/corners_found13.jpg
./camera_cal/calibration14.jpg
./output_images/camera_calib/corners_found14.jpg
./camera_cal/calibration15.jpg
./output_images/camera_calib/corners_found15.jpg
./camera_cal/calibration16.jpg
./output_images/camera_calib/corners_found16.jpg
./camera_cal/calibration17.jpg
./output_images/camera_calib/corners_found17.jpg
./camera_cal/calibration18.jpg
./output_images/camera_calib/corners_found18.jpg
./camera_cal/calibration19.jpg
./output_images/camera_calib/corners_found19.jpg
./camera_cal/calibration20.jpg
./output_images/camera_calib/corners_found20.jpg
In [3]:
# Test undistortion on an image
img = cv2.imread('camera_cal/calibration1.jpg')
img_size = (img.shape[1], img.shape[0])

# Do camera calibration given object points and image points
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, img_size,None,None)
dst = cv2.undistort(img, mtx, dist, None, mtx)

f, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,10))
ax1.imshow(img)
ax1.set_title('Original Image', fontsize=30)
ax2.imshow(dst)
ax2.set_title('Undistorted Image', fontsize=30)
Out[3]:
<matplotlib.text.Text at 0x7f366017d390>
In [4]:
# Save the camera calibration result for later use (we won't worry about rvecs / tvecs)
dist_pickle = {}
dist_pickle["mtx"] = mtx
dist_pickle["dist"] = dist
pickle.dump( dist_pickle, open( out_dir+"camera_dist_pickle.p", "wb" ) )
In [5]:
# Visualize undistortion
# Step through the list and search for chessboard corners
# load pickled distortion matrix
plt.figure(figsize=(12,30))

with open(out_dir+'camera_dist_pickle.p', mode='rb') as f:
    dist_pickle = pickle.load(f)
    mtx = dist_pickle["mtx"]
    dist = dist_pickle["dist"]
# Visualize undistortion on test images
for i in range(20):
    plt.subplot(10,2,i+1)
    
    fname = './camera_cal/calibration'+str(i+1)+'.jpg'
    print(fname)
    img = cv2.imread(fname)
    dst = cv2.undistort(img, mtx, dist, None, mtx)
    savefname = 'undistortion'+str(i+1)+'.jpg'
    write_name = out_dir+savefname
    cv2.imwrite(write_name,dst)
    plt.title(savefname,fontsize=10)
    plt.axis('off')
    plt.imshow(img)
./camera_cal/calibration1.jpg
./camera_cal/calibration2.jpg
./camera_cal/calibration3.jpg
./camera_cal/calibration4.jpg
./camera_cal/calibration5.jpg
./camera_cal/calibration6.jpg
./camera_cal/calibration7.jpg
./camera_cal/calibration8.jpg
./camera_cal/calibration9.jpg
./camera_cal/calibration10.jpg
./camera_cal/calibration11.jpg
./camera_cal/calibration12.jpg
./camera_cal/calibration13.jpg
./camera_cal/calibration14.jpg
./camera_cal/calibration15.jpg
./camera_cal/calibration16.jpg
./camera_cal/calibration17.jpg
./camera_cal/calibration18.jpg
./camera_cal/calibration19.jpg
./camera_cal/calibration20.jpg
In [6]:
def undistort(img):
    result = cv2.undistort(img, mtx, dist, None, mtx)
    return result

def binarize(img, s_thresh=(120, 255), sx_thresh=(20, 255),l_thresh=(40,255)):
    img = np.copy(img)
    
    # Convert to HLS color space and separate the V channel
    hls = cv2.cvtColor(img, cv2.COLOR_RGB2HLS).astype(np.float)
    #h_channel = hls[:,:,0]
    l_channel = hls[:,:,1]
    s_channel = hls[:,:,2]
    # Sobel x
    # sobelx = abs_sobel_thresh(img, orient='x', sobel_kernel=3, thresh=(0, 255))
    # l_channel_col=np.dstack((l_channel,l_channel, l_channel))
    sobelx = cv2.Sobel(l_channel, cv2.CV_64F, 1, 0) # Take the derivative in x
    abs_sobelx = np.absolute(sobelx) # Absolute x derivative to accentuate lines away from horizontal
    scaled_sobel = np.uint8(255*abs_sobelx/np.max(abs_sobelx))
    
    # Threshold x gradient
    sxbinary = np.zeros_like(scaled_sobel)
    sxbinary[(scaled_sobel >= sx_thresh[0]) & (scaled_sobel <= sx_thresh[1])] = 1
    
    # Threshold saturation channel
    s_binary = np.zeros_like(s_channel)
    s_binary[(s_channel >= s_thresh[0]) & (s_channel <= s_thresh[1])] = 1

    # Threshold lightness
    l_binary = np.zeros_like(l_channel)
    l_binary[(l_channel >= l_thresh[0]) & (l_channel <= l_thresh[1])] = 1
    
    channels = 255*np.dstack(( l_binary, sxbinary, s_binary)).astype('uint8')        
    binary = np.zeros_like(sxbinary)
    binary[((l_binary == 1) & (s_binary == 1) | (sxbinary==1))] = 1
    binary = 255*np.dstack((binary,binary,binary)).astype('uint8')            
    return  binary,channels
In [7]:
img = plt.imread('test_images/test5.jpg')

shape = img.shape
binary,channels = binarize(img)
plt.imsave(out_dir+'S_binary.jpg',binary)
plt.imsave(out_dir+'HLS_channels.jpg',channels)

# Plot the result
f, (ax1,ax2) = plt.subplots(1, 2, figsize=(24, 9))
f.tight_layout()

ax1.imshow(binary)
ax1.set_title('S channel Binary of HLS Color', fontsize=40)

ax2.imshow(channels)
ax2.set_title('HLS_Channels', fontsize=40)
Out[7]:
<matplotlib.text.Text at 0x7f366081b240>
In [8]:
def warp(img,tobird=True):
    corners = np.float32([[190,720],[589,457],[698,457],[1145,720]])
    new_top_left=np.array([corners[0,0],0])
    new_top_right=np.array([corners[3,0],0])
    offset=[150,0]
    
    img_size = (img.shape[1], img.shape[0])
    src = np.float32([corners[0],corners[1],corners[2],corners[3]])
    dst = np.float32([corners[0]+offset,new_top_left+offset,new_top_right-offset ,corners[3]-offset])    
    if tobird:
        M = cv2.getPerspectiveTransform(src, dst)
    else:
        M = cv2.getPerspectiveTransform(dst,src)
    warped = cv2.warpPerspective(img, M, img_size , flags=cv2.INTER_LINEAR)    
    return warped, M
In [9]:
img=plt.imread('./test_images/straight_lines1.jpg')
corners = np.float32([[190,720],[589,457],[698,457],[1145,720]])

img = cv2.undistort(img, mtx, dist, None, mtx)
imshape = img.shape

corner_tuples=[]
for ind,c in enumerate(corners):
    corner_tuples.append(tuple(corners[ind]))

cv2.line(img, corner_tuples[0], corner_tuples[1], color=[255,0,0], thickness=1)
cv2.line(img, corner_tuples[1], corner_tuples[2], color=[255,0,0], thickness=1)
cv2.line(img, corner_tuples[2], corner_tuples[3], color=[255,0,0], thickness=1)
cv2.line(img, corner_tuples[3], corner_tuples[0], color=[255,0,0], thickness=1)

warped,_ = warp(img) 
plt.imsave(out_dir+'lane_roi.jpg',img)
plt.imsave(out_dir+'lane_roi_warped.jpg',warped)

# Plot the result
f, (ax1,ax2) = plt.subplots(1, 2, figsize=(24, 9))
f.tight_layout()

ax1.imshow(img)
ax1.set_title('Original image and roi area(red)', fontsize=40)

ax2.imshow(warped)
ax2.set_title('Warped image and roi area(red)', fontsize=40)
Out[9]:
<matplotlib.text.Text at 0x7f366055f0b8>
In [10]:
def region_of_interest(img):
    """
    Applies an image mask.
    
    Only keeps the region of the image defined by the polygon
    formed from `vertices`. The rest of the image is set to black.
    """    
    shape = img.shape
    vertices = np.array([[(0,0),(shape[1],0),(shape[1],0),(6*shape[1]/7,shape[0]),
                      (shape[1]/7,shape[0]), (0,0)]],dtype=np.int32)

    mask = np.zeros_like(img)   
    
    #defining a 3 channel or 1 channel color to fill the mask with depending on the input image
    if len(img.shape) > 2:
        channel_count = img.shape[2]  # i.e. 3 or 4 depending on your image
        ignore_mask_color = (255,) * channel_count
    else:
        ignore_mask_color = 255
        
    #filling pixels inside the polygon defined by "vertices" with the fill color    
    cv2.fillPoly(mask, vertices, ignore_mask_color)
    
    #returning the image only where mask pixels are nonzero
    masked_image = cv2.bitwise_and(img, mask)
    return masked_image

def warp_pipeline(img):
    undist = undistort(img)    
    result,_ = warp(undist)
    result = region_of_interest(result)
    return result
    
def warp_binarize_pipeline(img):
    undist = undistort(img)
    binary,_  = binarize(undist)
    result,_  = warp(binary)
    result = region_of_interest(result)
    return result 

warp_roi = warp_pipeline(img)
warp_binary_roi = warp_binarize_pipeline(img)

plt.imsave(out_dir+'warp_roi.jpg',warp_roi)
plt.imsave(out_dir+'warp_binary_roi.jpg',warp_binary_roi)

# Plot the result
f, (ax1,ax2) = plt.subplots(1, 2, figsize=(24, 9))
f.tight_layout()

ax1.imshow(warp_roi)
ax1.set_title('Warped ROI', fontsize=40)

ax2.imshow(warp_binary_roi)
ax2.set_title('Warped binary ROI', fontsize=40)
Out[10]:
<matplotlib.text.Text at 0x7f3660298a58>
In [11]:
# now back to the test image
img=plt.imread('./test_images/test5.jpg')
warped = warp_pipeline(img)
warped_binary = warp_binarize_pipeline(img)

plt.imsave(out_dir+'warp_test5.jpg',warped)
plt.imsave(out_dir+'warp_binary_test5.jpg',warped_binary)

# Plot the result
f, (ax1,ax2) = plt.subplots(1, 2, figsize=(24, 9))
f.tight_layout()

ax1.imshow(warped)
ax1.set_title('Warped ROI', fontsize=40)

ax2.imshow(warped_binary)
ax2.set_title('Warped binary ROI', fontsize=40)
Out[11]:
<matplotlib.text.Text at 0x7f366037bac8>
In [12]:
def find_peaks(img,thresh):
    half_ss = int(img.shape[0]/2)
    #print(half_ss)
    img_half=img[half_ss:,:,0]
    data = np.sum(img_half, axis=0)
    filtered = scipy.ndimage.filters.gaussian_filter1d(data,20)
    xs = np.arange(len(filtered))
    peak_ind = signal.find_peaks_cwt(filtered, np.arange(20,300))
    peaks = np.array(peak_ind)
    peaks = peaks[filtered[peak_ind]>thresh]
    return peaks,filtered

def get_next_window(img,center_point,width):
    """
    input: img,center_point,width
        img: binary 3 channel image
        center_point: center of window
        width: width of window
    
    output: masked,center_point
        masked : a masked image of the same size. mask is a window centered at center_point
        center : the mean ofall pixels found within the window
    """
    
    ny,nx,_ = img.shape
    mask  = np.zeros_like(img)
    if (center_point <= width/2): center_point = width/2
    if (center_point >= nx-width/2): center_point = nx-width/2
    
    left  = center_point - width/2
    right = center_point + width/2
    
    vertices = np.array([[(left,0),(left,ny), (right,ny),(right,0)]], dtype=np.int32)
    ignore_mask_color=(255,255,255)
    cv2.fillPoly(mask, vertices, ignore_mask_color)
    masked = cv2.bitwise_and(mask,img)

    hist = np.sum(masked[:,:,0],axis=0)
    if max(hist>10000):
        center = np.argmax(hist)
    else:
        center = center_point
        
    return masked,center

def lane_from_window(binary,center_point,width):
    n_zones=6
    ny,nx,nc = binary.shape
    zones = binary.reshape(n_zones,-1,nx,nc)
    zones = zones[::-1] # start from the bottom slice
    window,center = get_next_window(zones[0],center_point,width)
    
    for zone in zones[1:]:
        next_window,center = get_next_window(zone,center,width)
        window = np.vstack((next_window,window))
    
    return window
In [13]:
left_binary = lane_from_window(warped_binary,380,300)
right_binary = lane_from_window(warped_binary,1000,300)

plt.imsave(out_dir+'left_lane.jpg',left_binary)
plt.imsave(out_dir+'right_lane.jpg',right_binary)

# Plot the result
f, (ax1,ax2) = plt.subplots(1, 2, figsize=(24, 9))
f.tight_layout()

ax1.imshow(left_binary)
ax1.set_title('Left Lane', fontsize=40)

ax2.imshow(right_binary)
ax2.set_title('Right Lane', fontsize=40)
Out[13]:
<matplotlib.text.Text at 0x7f3660623f60>
In [14]:
# Define a class to receive the characteristics of each line detection
class Line:
    def __init__(self,n=5):
        # length of queue to store data
        self.n = n
        #number of fits in buffer
        self.n_buffered = 0
        # was the line detected in the last iteration?
        self.detected = False  
        # x values of the last n fits of the line
        self.recent_xfitted = deque([],maxlen=n)
        #average x values of the fitted line over the last n iterations
        self.avgx = None
        # fit coeffs of the last n fits
        self.recent_fit_coeffs = deque([],maxlen=n)        
        #polynomial coefficients averaged over the last n iterations
        self.avg_fit_coeffs = None  
        # xvals of the most recent fit
        self.current_fit_xvals = [np.array([False])]  
        #polynomial coefficients for the most recent fit
        self.current_fit_coeffs = [np.array([False])]          
        #x values for detected line pixels
        self.allx = None  
        #y values for detected line pixels
        self.ally = None
        #y values for line fit
        self.fit_yvals = np.linspace(0, 100, num=101)*7.2  # always the same y-range as image
        #radius of curvature of the line in some units
        self.radius_of_curvature = None 
        # origin (pixels) of fitted line at the bottom of the image
        self.line_pos = None 
        #distance in meters of vehicle center from the line
        self.line_base_pos = None 
        #difference in fit coefficients between last and new fits
        self.diffs = np.array([0,0,0], dtype='float') 

    def set_current_fit_xvals(self):
        yvals = self.fit_yvals
        self.current_fit_xvals = self.current_fit_coeffs[0]*yvals**2 + self.current_fit_coeffs[1]*yvals + self.current_fit_coeffs[2]
        
    def add_data(self):
        self.recent_xfitted.appendleft(self.current_fit_xvals)
        self.recent_fit_coeffs.appendleft(self.current_fit_coeffs)
        assert len(self.recent_xfitted)==len(self.recent_fit_coeffs)
        self.n_buffered = len(self.recent_xfitted)
        
    def pop_data(self):        
        if self.n_buffered>0:
            self.recent_xfitted.pop()
            self.recent_fit_coeffs.pop()
            assert len(self.recent_xfitted)==len(self.recent_fit_coeffs)
            self.n_buffered = len(self.recent_xfitted)
        
        return self.n_buffered
        
    def set_avgx(self):
        fits = self.recent_xfitted
        if len(fits)>0:
            avg=0
            for fit in fits:
                avg +=np.array(fit)
            avg = avg / len(fits)
            self.avgx = avg
            
    def set_avgcoeffs(self):
        coeffs = self.recent_fit_coeffs
        if len(coeffs)>0:
            avg=0
            for coeff in coeffs:
                avg +=np.array(coeff)
            avg = avg / len(coeffs)
            self.avg_fit_coeffs = avg
    
    def set_allxy(self,lane_candidate):
        self.ally,self.allx = (lane_candidate[:,:,0]>254).nonzero()

    def set_current_fit_coeffs(self):
        self.current_fit_coeffs = np.polyfit(self.ally, self.allx, 2)
    
    def get_diffs(self):
        if self.n_buffered>0:
            self.diffs = self.current_fit_coeffs - self.avg_fit_coeffs
        else:
            self.diffs = np.array([0,0,0], dtype='float')                 
            
    def set_radius_of_curvature(self):
        # Define y-value where we want radius of curvature (choose bottom of the image)
        y_eval = max(self.fit_yvals)
        if self.avg_fit_coeffs is not None:
            self.radius_of_curvature = ((1 + (2*self.avg_fit_coeffs[0]*y_eval + self.avg_fit_coeffs[1])**2)**1.5) \
                             /np.absolute(2*self.avg_fit_coeffs[0])
                        
            
    def set_line_base_pos(self):
        y_eval = max(self.fit_yvals)
        self.line_pos = self.current_fit_coeffs[0]*y_eval**2 \
                        +self.current_fit_coeffs[1]*y_eval \
                        + self.current_fit_coeffs[2]
        basepos = 640
        
        self.line_base_pos = (self.line_pos - basepos)*3.7/600.0 # 3.7 meters is about 600 pixels in the x direction

    # here come sanity checks of the computed metrics
    def accept_lane(self):
        flag = True
        maxdist = 2.8  # distance in meters from the lane
        if(abs(self.line_base_pos) > maxdist ):
            print('lane too far away')
            flag  = False        
        if(self.n_buffered > 0):
            relative_delta = self.diffs / self.avg_fit_coeffs
            # allow maximally this percentage of variation in the fit coefficients from frame to frame
            if not (abs(relative_delta)<np.array([0.7,0.5,0.15])).all():
                print('fit coeffs too far off [%]',relative_delta)
                flag=False
                
        return flag
    
    def update(self,lane):
        self.set_allxy(lane)
        self.set_current_fit_coeffs()
        self.set_current_fit_xvals()
        self.set_radius_of_curvature()
        self.set_line_base_pos()
        self.get_diffs()
        if self.accept_lane():
            self.detected=True
            self.add_data()
            self.set_avgx()
            self.set_avgcoeffs()            
        else:
            self.detected=False            
            self.pop_data()
            if self.n_buffered>0:
                self.set_avgx()
                self.set_avgcoeffs()
                    
        return self.detected,self.n_buffered
    
def get_binary_lane_image(img,line,window_center,width=300):
    if line.detected:
        window_center=line.line_pos
    else:
        peaks,filtered = find_peaks(img,thresh=3000)
        if len(peaks)!=2:
            print('Trouble ahead! '+ str(len(peaks)) +' lanes detected!')
            plt.imsave('troublesome_image.jpg',img)                        
            
        peak_ind = np.argmin(abs(peaks-window_center))
        peak  = peaks[peak_ind]
        window_center = peak
    
    lane_binary = lane_from_window(img,window_center,width)
    return lane_binary 
In [15]:
left=Line()
right=Line()

detected_l,n_buffered_left = left.update(left_binary)
detected_r,n_buffered_right = right.update(right_binary)

leftx = left.allx
left_fitx = left.current_fit_xvals
yvals_l = left.ally

rightx = right.allx
right_fitx = right.current_fit_xvals
yvals_r = right.ally

yvals = left.fit_yvals

plt.plot(rightx, yvals_r, '.', color='red')
plt.plot(right_fitx, yvals, color='green', linewidth=3)

plt.plot(leftx, yvals_l, '.', color='red')
plt.plot(left_fitx, yvals, color='green', linewidth=3)

plt.xlim(0, 1280)
plt.ylim(0, 720)
plt.gca().invert_yaxis()
plt.savefig(out_dir+'fitted_lanes.jpg')
plt.show()
In [16]:
def project_lane_lines(img,left_fitx,right_fitx,yvals):
    
    # Create an image to draw the lines on
    color_warp = np.zeros_like(img).astype(np.uint8)

    # Recast the x and y points into usable format for cv2.fillPoly()
    pts_left = np.array([np.transpose(np.vstack([left_fitx, yvals]))])
    pts_right = np.array([np.flipud(np.transpose(np.vstack([right_fitx, yvals])))])
    pts = np.hstack((pts_left, pts_right))

    # Draw the lane onto the warped blank image
    cv2.fillPoly(color_warp, np.int_([pts]), (0,255, 0))
    undist = undistort(img)    
    unwarp,Minv = warp(img,tobird=False)

    # Warp the blank back to original image space using inverse perspective matrix (Minv)
    newwarp = cv2.warpPerspective(color_warp, Minv, (img.shape[1], img.shape[0])) 
    # Combine the result with the original image
    result = cv2.addWeighted(undist, 1, newwarp, 0.3, 0)
    return result
In [17]:
def process_image(img):
    global left
    global right
    undist = undistort(img)
    binary,_  = binarize(undist)
    warped,_  = warp(binary)
    warped_binary = region_of_interest(warped)
    
    window_center_l = 340
    if left.detected:
        window_center_l = left.line_pos    
        
    left_binary = get_binary_lane_image(warped_binary,left,window_center_l,width=300)
    
    window_center_r = 940
    if right.detected:
        window_center_r = right.line_pos   
        
    right_binary = get_binary_lane_image(warped_binary,right,window_center_r,width=300)
    
    detected_l,n_buffered_left = left.update(left_binary)
    detected_r,n_buffered_right = right.update(right_binary)    
    
    detected_l,n_buffered_left = left.update(left_binary)
    detected_r,n_buffered_right = right.update(right_binary) 
    
    left_fitx = left.avgx
    right_fitx = right.avgx
    yvals = left.fit_yvals
    lane_width = 3.7
    off_center = -1*round(0.5*(right.line_base_pos-lane_width/2) +  0.5*(abs(left.line_base_pos)-lane_width/2),2)
    
    result = project_lane_lines(img,left_fitx,right_fitx,yvals)
    
    font = cv2.FONT_HERSHEY_SIMPLEX
    str1 = str('Distance from center: '+str(off_center)+'m')
    cv2.putText(result,str1,(430,630), font, 1,(0,0,255),2,cv2.LINE_AA)
    
    cnt_int = 0
    curvature = 0
    
    if left.radius_of_curvature:
        curvature = curvature + left.radius_of_curvature
        cnt_int = cnt_int + 1
        
    if right.radius_of_curvature:
        curvature = curvature + right.radius_of_curvature
        cnt_int = cnt_int + 1
        
    if cnt_int > 0:
        curvature = int(curvature / cnt_int)
    
        str2 = str('Radius of curvature: '+str(curvature)+'m')
        cv2.putText(result,str2,(430,670), font, 1,(0,0,255),2,cv2.LINE_AA)
    
    return result
In [18]:
img = plt.imread('./test_images/test3.jpg')
#left = Line(7)
#right = Line(7)

left = Line()
right = Line()

result = process_image(img)

plt.figure()
plt.imshow(result)
plt.show()
plt.imsave(out_dir+'detected_lane_test3.jpg',result)
In [19]:
import glob

image_path = glob.glob('./test_images/*.jpg')

for image_names in image_path:
    
    image = mpimg.imread(image_names)
    
    print('This image path/name is:', image_names, 'with dimesions:', image.shape)
    left = Line()
    right = Line()
    
    save_image_names = './output_images/test_results/detected_lane_'+image_names[14:-4]+'.jpg'
    print('This save image path/name is:', save_image_names)

    result = process_image(image) 
    plt.imshow(result)
    plt.show()
    
    mpimg.imsave(save_image_names, result)
This image path/name is: ./test_images/straight_lines1.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_straight_lines1.jpg
This image path/name is: ./test_images/test6.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_test6.jpg
This image path/name is: ./test_images/test3.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_test3.jpg
This image path/name is: ./test_images/test2.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_test2.jpg
This image path/name is: ./test_images/test5.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_test5.jpg
This image path/name is: ./test_images/test1.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_test1.jpg
This image path/name is: ./test_images/test4.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_test4.jpg
This image path/name is: ./test_images/straight_lines2.jpg with dimesions: (720, 1280, 3)
This save image path/name is: ./output_images/test_results/detected_lane_straight_lines2.jpg
In [20]:
out_dir='./output_images/test_results/'
output = out_dir+'detected_lane_project_video.mp4'
clip = VideoFileClip("project_video.mp4")
out_clip = clip.fl_image(process_image) 
%time out_clip.write_videofile(output, audio=False)
fit coeffs too far off [%] [ -8.36657386  13.22141653  -0.24421143]
fit coeffs too far off [%] [ 42.06560703  -7.70821875  -0.09554776]
fit coeffs too far off [%] [ -8.36657386  13.22141653  -0.24421143]
fit coeffs too far off [%] [ 42.06560703  -7.70821875  -0.09554776]
[MoviePy] >>>> Building video ./output_images/test_results/detected_lane_project_video.mp4
[MoviePy] Writing video ./output_images/test_results/detected_lane_project_video.mp4
  1%|          | 14/1261 [00:01<02:34,  8.08it/s]
fit coeffs too far off [%] [ 1.77226216  0.49229643 -0.02644851]
fit coeffs too far off [%] [ 1.79906086  0.53083553 -0.03048615]
fit coeffs too far off [%] [ 1.48278643  0.55033984 -0.04889713]
fit coeffs too far off [%] [ 1.44441654  0.52701889 -0.04610914]
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fit coeffs too far off [%] [ 1.02507872  0.46314854 -0.05605895]
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fit coeffs too far off [%] [ 1.18974657  0.316171   -0.03452969]
fit coeffs too far off [%] [ 1.51453206  0.33824985 -0.03135685]
fit coeffs too far off [%] [ 1.16149778  0.30419305 -0.03820271]
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fit coeffs too far off [%] [ 1.06302603  0.28916682 -0.03453975]
fit coeffs too far off [%] [ 1.39624012  0.31168451 -0.02502841]
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fit coeffs too far off [%] [ 0.79811304  0.32164256 -0.02016147]
fit coeffs too far off [%] [ 0.85451072  0.34860037 -0.0230346 ]
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fit coeffs too far off [%] [-0.89148745 -0.38524788  0.03453947]
fit coeffs too far off [%] [-0.88931288 -0.37987477  0.03355998]
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fit coeffs too far off [%] [ 0.7480971   0.39461985 -0.04107473]
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fit coeffs too far off [%] [ 0.83966696  0.49122986 -0.03314302]
fit coeffs too far off [%] [ 0.79860689  0.48506991 -0.03475285]
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fit coeffs too far off [%] [ 1.08801314  0.46751438 -0.04119749]
fit coeffs too far off [%] [ 1.12675531  0.47486864 -0.04120364]
fit coeffs too far off [%] [ 1.19196727  0.51769217 -0.04524524]
fit coeffs too far off [%] [ 1.26548594  0.54836958 -0.04819201]
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fit coeffs too far off [%] [ 0.93092239  0.39104233 -0.0315691 ]
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fit coeffs too far off [%] [ 0.86554463  0.26124639 -0.00429362]
fit coeffs too far off [%] [ 0.86228399  0.27175204 -0.0068428 ]
fit coeffs too far off [%] [ 1.27424831  0.45151718 -0.02147084]
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fit coeffs too far off [%] [ 1.39352463  0.51111217 -0.02719935]
fit coeffs too far off [%] [ 1.40419719  0.58736284 -0.04248928]
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fit coeffs too far off [%] [ 0.70714973  0.26992915 -0.0318013 ]
fit coeffs too far off [%] [ 0.74550687  0.28330431 -0.03278831]
fit coeffs too far off [%] [ 1.02366473  0.33162631 -0.02949635]
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fit coeffs too far off [%] [ 1.15092404  0.35701945 -0.03087435]
fit coeffs too far off [%] [ 1.13619757  0.41288887 -0.0476171 ]
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fit coeffs too far off [%] [-1.82650538 -0.66605486  0.02105953]
fit coeffs too far off [%] [-1.83869987 -0.66657993  0.02200691]
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fit coeffs too far off [%] [-1.78442539 -0.60792551  0.0096168 ]
fit coeffs too far off [%] [-1.79040641 -0.60828566  0.01010338]
fit coeffs too far off [%] [-1.27449717 -0.52476334  0.02003603]
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fit coeffs too far off [%] [-2.98414264  0.87830039 -0.02504046]
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fit coeffs too far off [%] [-0.82075225 -0.23926179  0.0035597 ]
fit coeffs too far off [%] [-0.81514237 -0.21868343  0.00156926]
fit coeffs too far off [%] [-0.7188527  -0.23712876  0.00531833]
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fit coeffs too far off [%] [-0.83360618 -0.2696512   0.0293175 ]
fit coeffs too far off [%] [-0.80847391 -0.22551604  0.02195931]
fit coeffs too far off [%] [ 1.44257109  0.07185044  0.00473414]
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fit coeffs too far off [%] [ 1.30818092  0.05849356  0.00614634]
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fit coeffs too far off [%] [-1.45657119 -0.19860162  0.00344019]
fit coeffs too far off [%] [ 1.89167509 -0.06703204  0.01953032]
fit coeffs too far off [%] [  2.11597454e+00  -2.76281744e-04   1.51159126e-02]
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fit coeffs too far off [%] [ 5.90371905  0.76479691 -0.00862122]
fit coeffs too far off [%] [ 4.90329301  0.89154686 -0.0143769 ]
fit coeffs too far off [%] [-2.12277732 -0.29511105  0.02011634]
fit coeffs too far off [%] [ 6.69594266  1.05366774 -0.00795972]
fit coeffs too far off [%] [-2.28089827 -0.27785948  0.0179043 ]
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fit coeffs too far off [%] [-4.48717299 -0.60400498  0.03957773]
fit coeffs too far off [%] [-5.50778923 -0.55541574  0.02754875]
fit coeffs too far off [%] [-6.93998858 -0.57206816  0.02266004]
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fit coeffs too far off [%] [-0.18985613  0.72663398 -0.01756371]
fit coeffs too far off [%] [-0.22738075  0.93768672 -0.01894337]
fit coeffs too far off [%] [-0.31835724  0.68109799 -0.00976814]
fit coeffs too far off [%]
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 [-0.28127441  0.59433365 -0.01052739]
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fit coeffs too far off [%] [-0.22030439  0.86361138 -0.03112349]
fit coeffs too far off [%] [-0.22101167  0.79708977 -0.02884196]
fit coeffs too far off [%] [-0.60980421  0.69189029 -0.0105709 ]
fit coeffs too far off [%] [-1.20354196 -0.60278979  0.00461158]
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fit coeffs too far off [%] [-0.60922575  0.74177177 -0.01068839]
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fit coeffs too far off [%] [-1.02140753  0.7343683   0.00163982]
fit coeffs too far off [%] [ 0.69679714  0.70491606 -0.017423  ]
fit coeffs too far off [%] [ 1.00449896  1.06993492 -0.02359996]
fit coeffs too far off [%] [ 10.14636705  -0.31591071   0.03090003]
fit coeffs too far off [%] [ 0.35708971  1.01616564 -0.0375588 ]
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fit coeffs too far off [%] [-2.65060966 -0.94592262  0.02087796]
fit coeffs too far off [%] [ -1.27204765e+00   1.12519610e+01  -9.79533346e-03]
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fit coeffs too far off [%] [ 0.93256102  0.20516758 -0.00133384]
fit coeffs too far off [%] [-1.38506835  0.61486965 -0.02995599]
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fit coeffs too far off [%] [ 1.06002016 -0.11330912  0.00217034]
fit coeffs too far off [%] [-1.73191273 -0.75310966  0.02119288]
fit coeffs too far off [%] [-1.69844735 -0.74467974  0.01901451]
fit coeffs too far off [%] [  1.80937181e+00  -1.21383263e-01  -9.92886893e-04]
fit coeffs too far off [%] [-0.7281977  -0.55602779  0.01643432]
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fit coeffs too far off [%] [ 1.63052455 -1.67339566  0.03293675]
fit coeffs too far off [%] [-0.7249754  -0.09233183 -0.00525667]
fit coeffs too far off [%] [ 1.39177034 -1.7524935   0.03076322]
fit coeffs too far off [%] [-0.71524939 -0.00176518 -0.00745566]
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fit coeffs too far off [%] [ 1.22606564 -1.58864556  0.03018089]
fit coeffs too far off [%] [ -2.32652675e+00  -6.60209310e-01  -1.93476650e-03]
fit coeffs too far off [%] [-0.11695536  1.04896536  0.02760646]
fit coeffs too far off [%] [-2.76201059  5.5486367  -0.02253848]
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fit coeffs too far off [%] [-0.12760461 -0.55978476 -0.01670224]
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fit coeffs too far off [%] [-0.12552341 -1.56440034 -0.01506562]
fit coeffs too far off [%] [-0.17079414 -1.66449989 -0.01080047]
fit coeffs too far off [%] [-0.36827287 -3.65346397 -0.02688158]
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fit coeffs too far off [%] [-0.48876681 -0.51897404  0.01606401]
fit coeffs too far off [%] [-0.48620798 -0.50359884  0.01428182]
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fit coeffs too far off [%] [-0.55617113  0.77228899 -0.01507214]
fit coeffs too far off [%] [-0.57087937 -0.6232172   0.01555455]
fit coeffs too far off [%] [-0.44655013  0.69136191 -0.01796158]
fit coeffs too far off [%] [-0.50245894 -0.57739144  0.01379191]
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fit coeffs too far off [%] [-2.34367403  1.30955076 -0.01201207]
fit coeffs too far off [%] [-1.04187059 -0.75338146  0.00932013]
fit coeffs too far off [%] [-1.05490078 -0.70406856  0.00734895]
fit coeffs too far off [%] [-1.05637221 -1.03507981  0.01711981]
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fit coeffs too far off [%] [ 1.27536211  0.29518652 -0.00539277]
fit coeffs too far off [%] [ -8.78071560e+00  -1.05813357e+01  -3.67439043e-03]
fit coeffs too far off [%] [  1.54357001e+00   2.64697711e-01  -1.24737640e-03]
fit coeffs too far off [%] [ 2.75440981  0.55039857 -0.00846207]
fit coeffs too far off [%] [-0.76523181 -0.81264733  0.00269445]
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fit coeffs too far off [%] [  1.09802847e+01   4.13096968e+00   6.98226483e-03]
fit coeffs too far off [%] [ -1.31606233e+00  -1.86674384e+00  -1.37305760e-03]
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fit coeffs too far off [%] [-0.3688848   0.50104555  0.00518292]
fit coeffs too far off [%] [-2.44504354 -0.78064707 -0.00270293]
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fit coeffs too far off [%] [  7.34798856 -19.74776094  -0.01974969]
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fit coeffs too far off [%] [-1.02452463 -0.59262096  0.03324842]
fit coeffs too far off [%] [-1.02557124 -0.57974018  0.02998633]
fit coeffs too far off [%] [-1.20982292 -0.61055863  0.02542473]
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fit coeffs too far off [%] [-1.21639541 -0.61679307  0.02910437]
fit coeffs too far off [%] [-1.74560034 -0.85447164  0.03529598]
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fit coeffs too far off [%] [ 0.99509377 -3.07128379  0.02655847]
fit coeffs too far off [%] [ 0.30412361  0.62468316  0.00419237]
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fit coeffs too far off [%] [ 0.38298629  1.18874811  0.04419255]
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fit coeffs too far off [%] [ 0.69823639  0.52218296 -0.0048278 ]
fit coeffs too far off [%] [ 0.75207779  0.46541733 -0.00272067]
fit coeffs too far off [%] [  1.80271875e+00   8.81170267e-01  -6.36143418e-04]
fit coeffs too far off [%] [ 1.84758196  0.9997047  -0.00282989]
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fit coeffs too far off [%] [-1.13074145 -1.07729892  0.01166367]
fit coeffs too far off [%] [-1.13880975 -1.08356778  0.01038839]
fit coeffs too far off [%] [-0.98590896 -1.13813253  0.01297112]
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fit coeffs too far off [%] [-0.98264194 -1.14731458  0.01339505]
fit coeffs too far off [%] [-1.62262428 -1.3613562   0.00942718]
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fit coeffs too far off [%] [-1.74364477 -2.38166922 -0.00791652]
fit coeffs too far off [%] [-3.60745955 -0.73341561 -0.0090994 ]
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fit coeffs too far off [%] [-0.78053109 -0.35425161  0.00601262]
fit coeffs too far off [%] [  3.64142439e+00  -1.46665430e+01   8.59662174e-03]
fit coeffs too far off [%] [-0.7383616  -0.31729461  0.00329557]
fit coeffs too far off [%] [-1.328809   -0.61655582 -0.00165479]
fit coeffs too far off [%] [-1.34485386 -1.93050736 -0.01563098]
 30%|██▉       | 378/1261 [00:50<02:18,  6.38it/s]
fit coeffs too far off [%] [-1.46416364 -0.59565095 -0.00829232]
fit coeffs too far off [%] [-2.01802541 -0.97605007 -0.02282543]
 30%|███       | 381/1261 [00:50<02:09,  6.78it/s]
fit coeffs too far off [%] [  5.87768929e-01  -1.74689985e+01  -1.47191736e-02]
fit coeffs too far off [%] [ 0.75712289  0.31636634  0.0052876 ]
 30%|███       | 382/1261 [00:51<02:04,  7.07it/s]
fit coeffs too far off [%] [-0.41896683 -0.58480349  0.01101236]
fit coeffs too far off [%] [-0.4456244  -0.58838622  0.00982698]
fit coeffs too far off [%] [-0.87286855 -0.80924314  0.00422357]
 30%|███       | 383/1261 [00:51<02:17,  6.38it/s]
fit coeffs too far off [%] [-0.8624806  -0.7830177   0.00184398]
fit coeffs too far off [%] [-1.17833797 -1.16867951  0.00443849]
 31%|███       | 386/1261 [00:51<02:08,  6.81it/s]
fit coeffs too far off [%] [ 0.7547294   0.97144392  0.00213612]
 31%|███       | 388/1261 [00:51<01:59,  7.32it/s]
fit coeffs too far off [%] [-0.86088776 -0.49005771 -0.00161721]
fit coeffs too far off [%] [-0.84306144 -0.52185262 -0.00328667]
fit coeffs too far off [%] [ 0.70460028  0.65219397 -0.02500422]
fit coeffs too far off [%] [ 1.71623733  0.59162775  0.00235941]
 31%|███       | 389/1261 [00:52<02:14,  6.47it/s]
fit coeffs too far off [%] [ 0.98440255  0.62805984 -0.02190745]
fit coeffs too far off [%] [  2.44199638e+00   5.12043948e-01   2.05369959e-04]
 31%|███       | 390/1261 [00:52<02:44,  5.31it/s]
fit coeffs too far off [%] [ 0.62024205  0.82246189 -0.0396121 ]
fit coeffs too far off [%] [ -1.96348807e+00  -3.29702982e-01   2.48868595e-04]
fit coeffs too far off [%] [ 0.65413979  0.82977915 -0.04059473]
fit coeffs too far off [%] [ 0.65228834  0.89289387 -0.0459392 ]
 31%|███       | 392/1261 [00:52<02:32,  5.68it/s]
fit coeffs too far off [%] [ -3.43593885e+00   9.00171001e-01  -8.58781959e-04]
 31%|███▏      | 395/1261 [00:53<02:02,  7.04it/s]
fit coeffs too far off [%] [-1.31728777 -1.14578925 -0.00987259]
fit coeffs too far off [%] [-1.30329585 -1.15413486 -0.00809542]
 32%|███▏      | 399/1261 [00:53<01:57,  7.34it/s]
fit coeffs too far off [%] [ 0.87357922  0.90899843  0.0069773 ]
fit coeffs too far off [%] [ 0.98976165  0.9190147   0.00651881]
fit coeffs too far off [%] [ 2.68179706  1.88956626  0.00860118]
 32%|███▏      | 400/1261 [00:53<02:13,  6.44it/s]
fit coeffs too far off [%] [ 2.06287175  1.63155865  0.00879136]
fit coeffs too far off [%] [ 2.67787567  2.08487426  0.01299611]
 32%|███▏      | 403/1261 [00:54<02:04,  6.87it/s]
fit coeffs too far off [%] [-0.67045011 -0.52461428 -0.01024169]
fit coeffs too far off [%] [-0.65164402 -0.50491066 -0.00988499]
fit coeffs too far off [%] [-0.91958493 -0.14481667 -0.00470779]
fit coeffs too far off [%] [-0.91392788 -0.13473007 -0.00478085]
 32%|███▏      | 405/1261 [00:54<02:26,  5.83it/s]
fit coeffs too far off [%] [-0.95816342 -0.18166591  0.00513744]
fit coeffs too far off [%] [ -9.43611524e-01  -1.30952580e-01   7.13908014e-04]
fit coeffs too far off [%] [-1.35216248 -0.12253909 -0.01267017]
 32%|███▏      | 408/1261 [00:55<02:09,  6.59it/s]
fit coeffs too far off [%] [ 1.25647725 -0.06451899 -0.00339644]
fit coeffs too far off [%] [-1.50685245 -0.98842151 -0.01280619]
fit coeffs too far off [%] [-1.47989564 -0.9891653  -0.01452431]
 32%|███▏      | 409/1261 [00:55<02:20,  6.06it/s]
fit coeffs too far off [%] [  1.73151270e+00  -1.73393775e-01  -2.52666514e-04]
fit coeffs too far off [%] [-1.56538108 -1.05344875 -0.0159319 ]
fit coeffs too far off [%] [  2.00699138e+00  -1.77232534e-01   8.62045316e-05]
fit coeffs too far off [%] [-1.63297085 -1.05621893 -0.01571509]
 33%|███▎      | 411/1261 [00:55<02:27,  5.76it/s]
fit coeffs too far off [%] [-1.08140579 -0.85273862 -0.0188686 ]
fit coeffs too far off [%] [ -3.41744284e+00   1.16315003e+00   2.03020657e-03]
 33%|███▎      | 413/1261 [00:56<02:06,  6.70it/s]
fit coeffs too far off [%] [  3.42978474e+00   1.09019240e+00   2.10075848e-03]
 33%|███▎      | 414/1261 [00:56<02:00,  7.01it/s]
fit coeffs too far off [%] [ -1.79597078e+00   9.14103121e-02  -1.41672178e-03]
fit coeffs too far off [%] [ 1.25649564  0.89516832  0.00519219]
fit coeffs too far off [%] [-1.85119954  0.09766038 -0.0018853 ]
fit coeffs too far off [%] [ 0.98345138  0.77289035  0.00509707]
 33%|███▎      | 415/1261 [00:56<02:31,  5.59it/s]
fit coeffs too far off [%] [-5.61053202  0.18516576  0.01843497]
fit coeffs too far off [%] [-5.48277408  0.20221657  0.01818895]
fit coeffs too far off [%] [-4.88011408  0.33039083 -0.00863819]
 33%|███▎      | 418/1261 [00:56<02:09,  6.51it/s]
fit coeffs too far off [%] [ 0.78696903  0.12651234  0.00421588]
 33%|███▎      | 419/1261 [00:56<02:02,  6.88it/s]
fit coeffs too far off [%] [-1.52755413 -1.1529069  -0.00749157]
fit coeffs too far off [%] [-1.50249731 -1.15317098 -0.00643203]
fit coeffs too far off [%] [-1.28827945 -1.11447403 -0.01117387]
 33%|███▎      | 420/1261 [00:57<02:15,  6.21it/s]
fit coeffs too far off [%] [-1.27972429 -1.10838895 -0.01231443]
fit coeffs too far off [%] [-0.83379893 -0.72852178 -0.00941833]
 34%|███▎      | 423/1261 [00:57<02:03,  6.80it/s]
fit coeffs too far off [%] [ 2.67714878  0.37072365 -0.00779192]
 34%|███▎      | 425/1261 [00:57<01:54,  7.33it/s]
fit coeffs too far off [%] [ 0.40541234  0.53507001  0.00346088]
fit coeffs too far off [%] [ 1.10926602  0.70244707  0.00137328]
fit coeffs too far off [%] [ 0.96536165  0.6109734   0.00119331]
 34%|███▍      | 427/1261 [00:58<02:01,  6.87it/s]
fit coeffs too far off [%] [ 0.83812359  0.99337315  0.01238898]
 34%|███▍      | 430/1261 [00:58<01:53,  7.31it/s]
fit coeffs too far off [%] [-1.11420077 -0.68124366 -0.00669425]
fit coeffs too far off [%] [-1.11534656 -0.67480459 -0.0058698 ]
fit coeffs too far off [%] [ -1.83612645e+00  -9.81470599e-01  -1.61212443e-03]
 34%|███▍      | 431/1261 [00:58<02:07,  6.50it/s]
fit coeffs too far off [%] [ -1.79332009e+00  -9.81742537e-01  -4.55507576e-04]
fit coeffs too far off [%] [-1.64576436 -0.16576929 -0.00474924]
fit coeffs too far off [%] [-1.38821969 -0.82718933 -0.0023472 ]
fit coeffs too far off [%] [ -1.65408207e+00  -1.79471059e-01  -2.70702424e-04]
 34%|███▍      | 434/1261 [00:59<02:12,  6.25it/s]
fit coeffs too far off [%] [ 2.80511465 -2.97580916  0.00447482]
fit coeffs too far off [%] [-2.76445422 -0.27245614  0.00539983]
fit coeffs too far off [%] [ -5.72258449e-01  -1.29806101e+00  -1.25258161e-03]
fit coeffs too far off [%] [-2.7073448  -0.29714829  0.01484629]
 34%|███▍      | 435/1261 [00:59<02:20,  5.87it/s]
fit coeffs too far off [%] [-4.8181497  -0.4754708   0.02851359]
fit coeffs too far off [%] [ -4.28259381e-01   1.99816493e+00   1.44724536e-03]
fit coeffs too far off [%] [-6.56969855 -0.47105133  0.03555005]
 35%|███▍      | 437/1261 [00:59<02:14,  6.14it/s]
fit coeffs too far off [%] [-7.09224396 -0.5894752   0.05524741]
fit coeffs too far off [%] [ -1.42810258e+00   8.79624997e-01  -7.81716255e-04]
fit coeffs too far off [%] [ 0.2210239  -0.56909849  0.0385376 ]
fit coeffs too far off [%] [ 1.9812402  -0.48340944 -0.01241317]
 35%|███▍      | 439/1261 [01:00<01:57,  6.97it/s]
fit coeffs too far off [%] [ 0.20655924 -1.28410218  0.03462568]
fit coeffs too far off [%] [-2.9906994  -1.77449776 -0.00966716]
fit coeffs too far off [%] [ 0.15831732 -1.27422246  0.04107366]
fit coeffs too far off [%] [-4.14439999 -1.71237473 -0.01191898]
 35%|███▍      | 441/1261 [01:00<02:13,  6.14it/s]
fit coeffs too far off [%] [ 0.08909109 -1.91057254  0.07373261]
fit coeffs too far off [%] [-10.82573584  -4.55982232  -0.02897674]
fit coeffs too far off [%] [  7.62059467e-01   5.16790011e-01  -4.28705322e-04]
 35%|███▌      | 443/1261 [01:00<01:57,  6.97it/s]
fit coeffs too far off [%] [ 0.05339671 -1.26266233 -0.05135287]
fit coeffs too far off [%] [ 0.05550982 -1.28214911 -0.0487934 ]
fit coeffs too far off [%] [-0.21020863 -1.69245504 -0.04407002]
 35%|███▌      | 444/1261 [01:00<02:10,  6.27it/s]
fit coeffs too far off [%] [-0.22630781 -1.62509441 -0.04415645]
fit coeffs too far off [%] [-0.01944155 -1.13061932 -0.05308781]
fit coeffs too far off [%] [-0.3708952  -0.60709426  0.00947294]
fit coeffs too far off [%] [-0.38734431 -0.58639813  0.00642868]
 35%|███▌      | 446/1261 [01:01<02:24,  5.64it/s]
fit coeffs too far off [%] [-0.14277528 -0.75466442  0.01373143]
fit coeffs too far off [%] [-0.62984185 -0.78009567  0.0043814 ]
fit coeffs too far off [%] [-0.62545971 -0.78742138  0.0058076 ]
fit coeffs too far off [%] [  1.80794676e-01  -4.95409221e+01   3.76940471e-02]
fit coeffs too far off [%] [-0.64957868 -0.56059239 -0.00459991]
 36%|███▌      | 449/1261 [01:01<02:06,  6.42it/s]
fit coeffs too far off [%] [-0.55479817 -0.61535452  0.00411965]
fit coeffs too far off [%] [ 6.49451538  7.35756923 -0.01396628]
 36%|███▌      | 451/1261 [01:01<01:53,  7.17it/s]
fit coeffs too far off [%] [-0.53579891 -0.52087373  0.00799625]
fit coeffs too far off [%] [ 1.08077654  1.0579745  -0.00696869]
 36%|███▌      | 456/1261 [01:02<01:42,  7.82it/s]
fit coeffs too far off [%] [-0.56655508 -0.59343558  0.0062727 ]
fit coeffs too far off [%] [-0.4874033  -0.55638897  0.00694245]
fit coeffs too far off [%] [-1.43889088 -0.8512382   0.00771864]
fit coeffs too far off [%] [-0.79192233 -0.86413275  0.00893309]
fit coeffs too far off [%] [-1.566527   -0.83579729  0.00627464]
 36%|███▌      | 457/1261 [01:02<01:59,  6.75it/s]
fit coeffs too far off [%] [-0.78092253 -0.85249695  0.00764991]
 36%|███▋      | 458/1261 [01:03<02:26,  5.47it/s]
fit coeffs too far off [%] [-2.38446188 -1.30173163  0.00622117]
fit coeffs too far off [%] [-0.73088599 -0.94671104  0.01147611]
fit coeffs too far off [%] [-2.58203827 -1.28375975  0.00400009]
fit coeffs too far off [%] [-6.6515877  -2.32619401  0.02278707]
fit coeffs too far off [%] [-1.43992473 -0.78118881 -0.00694315]
 37%|███▋      | 461/1261 [01:03<02:04,  6.45it/s]
fit coeffs too far off [%] [ -4.91966175e+00   2.56275242e+01   2.81647401e-03]
fit coeffs too far off [%] [ 0.28408318  0.91642944 -0.01113736]
fit coeffs too far off [%] [-2.91958838 -3.30604529  0.00660559]
fit coeffs too far off [%] [ 0.30359428  0.75572574 -0.0080478 ]
 37%|███▋      | 463/1261 [01:03<02:03,  6.45it/s]
fit coeffs too far off [%] [ 0.5972654   1.65534179 -0.02643846]
fit coeffs too far off [%] [ 0.08539262  0.61529465  0.00962396]
fit coeffs too far off [%] [-0.71596383 -0.14138055  0.00724759]
 37%|███▋      | 465/1261 [01:04<01:51,  7.14it/s]
fit coeffs too far off [%] [ 3.59831641  0.53332395 -0.00464109]
 38%|███▊      | 474/1261 [01:05<01:39,  7.92it/s]
fit coeffs too far off [%] [-1.0261135  -0.47336604  0.01527995]
fit coeffs too far off [%] [-1.03076668 -0.45110428  0.01644263]
fit coeffs too far off [%] [-0.78749642 -0.06466618 -0.01733428]
fit coeffs too far off [%] [-0.83137958 -0.14035881  0.00812188]
 38%|███▊      | 475/1261 [01:05<01:55,  6.80it/s]
fit coeffs too far off [%] [-0.72667848  0.00096642 -0.018108  ]
fit coeffs too far off [%] [-0.79713991 -0.08642805  0.00864127]
 38%|███▊      | 476/1261 [01:05<02:23,  5.47it/s]
fit coeffs too far off [%] [-0.97581082 -0.13115385 -0.00918154]
fit coeffs too far off [%] [-0.79934915 -0.14375737  0.0071394 ]
fit coeffs too far off [%] [-0.79946689 -0.11504478  0.00884688]
 38%|███▊      | 478/1261 [01:06<02:15,  5.78it/s]
fit coeffs too far off [%] [-1.0649094   0.22467215 -0.0217839 ]
fit coeffs too far off [%] [-1.14304727 -0.08546011  0.01765935]
fit coeffs too far off [%] [  3.88473481e+02  -8.47946388e-02  -6.47519236e-03]
fit coeffs too far off [%] [-5.42741     0.36997992  0.00648645]
 38%|███▊      | 480/1261 [01:06<01:57,  6.67it/s]
fit coeffs too far off [%] [-3.55100304 -0.7425966  -0.00875503]
fit coeffs too far off [%] [ 0.79627205 -0.03478962 -0.01532108]
fit coeffs too far off [%] [-0.20000064  0.69097889  0.00885098]
 38%|███▊      | 482/1261 [01:06<01:47,  7.27it/s]
fit coeffs too far off [%] [-0.88279566  0.78746167  0.00278151]
fit coeffs too far off [%] [ 0.98092817 -0.16285938 -0.01154202]
fit coeffs too far off [%] [ 2.20578016 -0.03496599  0.00563421]
fit coeffs too far off [%] [ 0.97696406 -0.1654164  -0.01074136]
 38%|███▊      | 483/1261 [01:06<02:00,  6.46it/s]
fit coeffs too far off [%] [ 1.27997699 -0.25422635 -0.0134738 ]
fit coeffs too far off [%] [ 2.33426966 -0.27149582 -0.01765637]
fit coeffs too far off [%] [ 0.7982596  -0.23961924  0.00095614]
fit coeffs too far off [%] [-1.23790717  0.12847362 -0.00361353]
 38%|███▊      | 484/1261 [01:06<02:09,  6.01it/s]
fit coeffs too far off [%] [-1.23425963  0.12907142 -0.00419032]
fit coeffs too far off [%] [ -3.40328586e+00   4.72925177e-01  -9.20605248e-04]
 39%|███▊      | 487/1261 [01:07<01:56,  6.64it/s]
fit coeffs too far off [%] [-1.12151883  0.23695095  0.01626381]
fit coeffs too far off [%] [-1.53489008 -0.55293416 -0.00976524]
fit coeffs too far off [%] [-1.12236125  0.31440466  0.01277088]
fit coeffs too far off [%] [-1.5583899  -0.5302156  -0.00659274]
 39%|███▊      | 488/1261 [01:07<02:23,  5.38it/s]
fit coeffs too far off [%] [-0.83736903 -0.31174862  0.04126967]
fit coeffs too far off [%] [-0.84095965 -0.16462476  0.0314996 ]
fit coeffs too far off [%] [-1.2734386  -0.15405451  0.04664194]
fit coeffs too far off [%] [-1.03332697 -0.58019659 -0.01481575]
 39%|███▉      | 489/1261 [01:07<02:25,  5.30it/s]
fit coeffs too far off [%] [-1.02988628 -0.58690948 -0.01283314]
fit coeffs too far off [%] [-2.31278432 -1.28356549 -0.02377275]
 39%|███▉      | 491/1261 [01:08<02:12,  5.79it/s]
fit coeffs too far off [%] [-9.59360627 -1.4335372   0.01445765]
fit coeffs too far off [%] [-0.38781304 -0.74809598  0.00076923]
fit coeffs too far off [%] [ -1.60267458e+01  -1.45321082e+00   1.46942802e-02]
fit coeffs too far off [%] [-4.24135163  0.27739145 -0.01409919]
 39%|███▉      | 493/1261 [01:08<02:07,  6.04it/s]
fit coeffs too far off [%] [ 0.07515045 -1.06324446  0.00822714]
fit coeffs too far off [%] [ -1.49701856e+00   2.90573701e-01  -1.04973237e-03]
fit coeffs too far off [%] [ -3.80711267e-01   3.08794005e+01   5.62983038e-04]
 39%|███▉      | 495/1261 [01:08<01:51,  6.88it/s]
fit coeffs too far off [%] [-3.81916796  0.1380162  -0.02139213]
fit coeffs too far off [%] [ 1.37214153 -0.17676521 -0.00472175]
fit coeffs too far off [%] [-0.17642438  0.76208006  0.00654675]
fit coeffs too far off [%] [-0.21366888  0.63105301  0.0043229 ]
 39%|███▉      | 497/1261 [01:09<01:54,  6.65it/s]
fit coeffs too far off [%] [-0.34095736  0.57416993  0.00074097]
fit coeffs too far off [%] [-5.01116664  2.75326654  0.00781956]
 39%|███▉      | 498/1261 [01:09<01:49,  6.95it/s]
fit coeffs too far off [%] [-1.12743616  0.11747067  0.01111054]
fit coeffs too far off [%] [-1.03151301 -0.73593259 -0.01545994]
fit coeffs too far off [%] [-1.14563844  0.07894411  0.01109782]
fit coeffs too far off [%] [-0.95217415  0.22185582 -0.00507224]
fit coeffs too far off [%] [-3.52569321  0.62517293  0.00735565]
 40%|███▉      | 499/1261 [01:09<02:01,  6.26it/s]
fit coeffs too far off [%] [-0.94711071  0.19939158 -0.00500664]
fit coeffs too far off [%] [-2.25383454  0.87993968 -0.03544126]
 40%|███▉      | 501/1261 [01:09<02:00,  6.30it/s]
fit coeffs too far off [%] [-0.70026658  0.08752152 -0.02001804]
fit coeffs too far off [%] [ 4.26227498  0.71330331  0.01354531]
fit coeffs too far off [%] [ 4.00568908  0.57803538  0.01023135]
fit coeffs too far off [%] [ 2.23740968  0.2747351  -0.02727606]
 40%|███▉      | 503/1261 [01:10<01:59,  6.36it/s]
fit coeffs too far off [%] [ 3.42364179  0.76157276  0.02158285]
fit coeffs too far off [%] [ 1.31832726 -0.00288673  0.02549673]
 40%|████      | 505/1261 [01:10<01:46,  7.08it/s]
fit coeffs too far off [%] [-1.40139892 -0.56566677 -0.01016454]
fit coeffs too far off [%] [-1.39636714 -0.55968177 -0.00875566]
fit coeffs too far off [%] [-0.90413943 -0.39567627 -0.00863597]
 40%|████      | 506/1261 [01:10<01:59,  6.30it/s]
fit coeffs too far off [%] [-0.89995821 -0.3974785  -0.0094648 ]
fit coeffs too far off [%] [-1.04091737 -0.4024257  -0.00671139]
 40%|████      | 509/1261 [01:10<01:50,  6.79it/s]
fit coeffs too far off [%] [ -6.75007795e+00   1.01043928e-01  -2.86875126e-03]
fit coeffs too far off [%] [ 4.1318444   0.39346842  0.00421332]
 40%|████      | 510/1261 [01:11<01:46,  7.08it/s]
fit coeffs too far off [%] [ 0.7505641   0.11659097 -0.00814673]
fit coeffs too far off [%] [ 1.43140317  0.15763911 -0.00896463]
 41%|████      | 511/1261 [01:11<02:02,  6.10it/s]
fit coeffs too far off [%] [ 0.97043931  0.09450003 -0.00619589]
fit coeffs too far off [%] [ 1.42802576  0.08475226 -0.00145106]
fit coeffs too far off [%] [ 1.24531114  0.06339137  0.00325857]
fit coeffs too far off [%] [-1.00112294 -0.4668055  -0.0116717 ]
 41%|████      | 512/1261 [01:11<02:10,  5.76it/s]
fit coeffs too far off [%] [-1.00117104 -0.45666946 -0.0106025 ]
fit coeffs too far off [%] [ 0.87714932 -0.00263975  0.0228777 ]
 41%|████      | 514/1261 [01:11<02:02,  6.10it/s]
fit coeffs too far off [%] [-0.77845312 -0.3704383  -0.00950548]
fit coeffs too far off [%] [-0.76714052 -0.34433964 -0.00735297]
fit coeffs too far off [%] [-3.5239126  -1.62130148 -0.02285536]
 41%|████      | 515/1261 [01:12<02:09,  5.77it/s]
fit coeffs too far off [%] [-3.80833511 -1.70164001 -0.01766924]
fit coeffs too far off [%] [-3.0268109  -1.18896718 -0.00704316]
 41%|████      | 517/1261 [01:12<02:02,  6.07it/s]
fit coeffs too far off [%] [-0.92269025 -0.07027699 -0.01792272]
fit coeffs too far off [%] [ 0.18593846  0.6191167   0.0021796 ]
fit coeffs too far off [%] [-0.92718104 -0.09165294 -0.0157239 ]
fit coeffs too far off [%] [-2.57825555 -0.53118313  0.0165638 ]
 41%|████      | 518/1261 [01:12<02:09,  5.73it/s]
fit coeffs too far off [%] [-0.23386214 -0.7821695   0.00081588]
fit coeffs too far off [%] [-2.65324728 -0.5434338   0.023865  ]
fit coeffs too far off [%] [-3.03736622 -0.58040024  0.0173855 ]
fit coeffs too far off [%] [-0.06790587 -3.76714619  0.0097173 ]
 41%|████▏     | 521/1261 [01:12<01:52,  6.55it/s]
fit coeffs too far off [%] [ -7.93104939e-01   2.30469583e+00  -1.05733203e-03]
fit coeffs too far off [%] [ -4.84856273e+00   7.42774186e-01   3.29213408e-03]
 41%|████▏     | 523/1261 [01:13<01:43,  7.16it/s]
fit coeffs too far off [%] [-0.85483078  0.47663897  0.00938371]
fit coeffs too far off [%] [-0.84217781  0.42625048  0.00786632]
 42%|████▏     | 524/1261 [01:13<01:58,  6.22it/s]
fit coeffs too far off [%] [-0.8648596   0.13163376  0.02868578]
fit coeffs too far off [%] [-1.65791121 -0.6764711  -0.00760995]
fit coeffs too far off [%] [-0.86644284  0.22534257  0.02417008]
fit coeffs too far off [%] [-1.65925255 -0.68244795 -0.00815295]
 42%|████▏     | 526/1261 [01:13<02:06,  5.80it/s]
fit coeffs too far off [%] [-1.13768286  0.20907814  0.0381334 ]
fit coeffs too far off [%] [-3.33532336  0.01996528 -0.02525906]
 42%|████▏     | 527/1261 [01:13<02:00,  6.10it/s]
fit coeffs too far off [%] [-0.81349924  0.41574444 -0.02066059]
fit coeffs too far off [%] [ -2.67985475e+00  -6.10193486e-01   2.38599136e-03]
fit coeffs too far off [%] [ -3.08475126e+00  -5.94868416e-01   2.85340808e-03]
 42%|████▏     | 528/1261 [01:14<02:12,  5.53it/s]
fit coeffs too far off [%] [-11.70514612   0.5772219   -0.03462837]
fit coeffs too far off [%] [-1.52371107  0.03970188  0.01744011]
fit coeffs too far off [%] [-1.47221826 -0.08253814  0.01216632]
fit coeffs too far off [%] [-1.26354775 -0.36713047  0.02857117]
 42%|████▏     | 530/1261 [01:14<02:02,  5.97it/s]
fit coeffs too far off [%] [-2.03567304 -0.36297618  0.00343766]
fit coeffs too far off [%] [-2.05306908 -0.17936163  0.04060579]
fit coeffs too far off [%] [ 7.21023778 -3.65572019 -0.04135629]
 42%|████▏     | 532/1261 [01:14<01:46,  6.85it/s]
fit coeffs too far off [%] [ 2.81341783  0.16805139  0.01089116]
fit coeffs too far off [%] [ 0.71837999  1.11867967 -0.0348055 ]
fit coeffs too far off [%] [-8.14120058 -3.67581872  0.13234488]
fit coeffs too far off [%] [ 0.3342702   0.53475136 -0.05293754]
 42%|████▏     | 534/1261 [01:15<01:38,  7.42it/s]
fit coeffs too far off [%] [-1.45168774 -1.16663006  0.06990473]
fit coeffs too far off [%] [-1.47555336 -1.17723777  0.06557261]
fit coeffs too far off [%] [-1.6477     -1.33507477  0.07774852]
 43%|████▎     | 537/1261 [01:15<01:40,  7.18it/s]
fit coeffs too far off [%] [-0.61923892 -0.74810475 -0.08276827]
fit coeffs too far off [%] [-0.6183572  -0.74151595 -0.07567436]
fit coeffs too far off [%] [-0.84985092 -1.07951841 -0.1235975 ]
 43%|████▎     | 538/1261 [01:15<01:53,  6.36it/s]
fit coeffs too far off [%] [-0.85471072 -1.07948536 -0.11699083]
 43%|████▎     | 540/1261 [01:16<01:54,  6.30it/s]
fit coeffs too far off [%] [-1.07535306 -1.35862748 -0.14156007]
fit coeffs too far off [%] [  2.91353753e+00   4.71831268e-01  -1.34693331e-03]
 43%|████▎     | 545/1261 [01:16<01:32,  7.75it/s]
fit coeffs too far off [%] [ 1.65874212  1.34874935  0.06899522]
fit coeffs too far off [%] [ 1.53380837  1.23857157  0.06593485]
fit coeffs too far off [%] [ 2.60389856  2.23262993  0.12785452]
 43%|████▎     | 546/1261 [01:16<01:47,  6.66it/s]
fit coeffs too far off [%] [ 2.52072868  2.18613543  0.12819501]
fit coeffs too far off [%] [ 1.83129481  1.73115062  0.11468456]
 44%|████▎     | 549/1261 [01:17<01:42,  6.96it/s]
fit coeffs too far off [%] [-0.85721355 -0.80576207 -0.11399362]
 44%|████▍     | 554/1261 [01:17<01:32,  7.66it/s]
fit coeffs too far off [%] [-1.20069316 -0.27375395  0.00392822]
fit coeffs too far off [%] [-1.21704581 -0.26444619  0.00275919]
fit coeffs too far off [%] [-3.05395703 -0.74752874 -0.0078904 ]
 44%|████▍     | 555/1261 [01:18<01:46,  6.63it/s]
fit coeffs too far off [%] [-3.54889852 -0.73575532 -0.0076816 ]
fit coeffs too far off [%] [-5.2576632  -1.29516689 -0.02873362]
 44%|████▍     | 558/1261 [01:18<01:43,  6.79it/s]
fit coeffs too far off [%] [-0.6890603  -2.9600301   0.02257763]
 44%|████▍     | 560/1261 [01:18<01:35,  7.34it/s]
fit coeffs too far off [%] [-0.65870036  0.21390371 -0.18277025]
fit coeffs too far off [%] [-1.16679539  0.55101213  0.06254417]
fit coeffs too far off [%] [-0.63213514  0.2190867  -0.1747921 ]
fit coeffs too far off [%] [-1.237108    0.44776302  0.05777999]
Trouble ahead! 3 lanes detected!
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.55807533  0.2566994  -0.20236281]
fit coeffs too far off [%] [-5.22336373  1.06898184  0.08158083]
fit coeffs too far off [%] [-0.51175484  0.23255723 -0.18304505]
fit coeffs too far off [%] [-6.79433207  0.99097351  0.07378648]
 44%|████▍     | 561/1261 [01:19<03:06,  3.76it/s]
Trouble ahead! 3 lanes detected!
 45%|████▍     | 562/1261 [01:19<04:08,  2.82it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.30688474  0.60380302 -0.2587147 ]
fit coeffs too far off [%] [-14.02758102   1.77125516   0.10780799]
 45%|████▍     | 564/1261 [01:20<02:47,  4.17it/s]
fit coeffs too far off [%] [-0.4329013  -0.32932776  0.21429811]
fit coeffs too far off [%] [-1.09677642 -0.71458896 -0.08926638]
fit coeffs too far off [%] [-1.10203405 -0.69531326 -0.07764995]
 45%|████▍     | 565/1261 [01:20<02:41,  4.30it/s]
fit coeffs too far off [%] [ 1.05800648  0.13855474  0.05221849]
fit coeffs too far off [%] [-1.5159013  -0.90361515 -0.10159934]
fit coeffs too far off [%] [ 1.02171936  0.27618246  0.0090276 ]
fit coeffs too far off [%] [-0.37227221 -0.54742041  0.15445769]
 45%|████▍     | 567/1261 [01:20<02:13,  5.20it/s]
fit coeffs too far off [%] [ 0.86866023 -2.90515754 -0.03662755]
fit coeffs too far off [%] [-0.82161034 -0.57420187  0.04018343]
fit coeffs too far off [%] [ 0.67808866  1.69798165 -0.03336949]
 45%|████▌     | 569/1261 [01:20<01:48,  6.35it/s]
fit coeffs too far off [%] [ 4.40061051  1.19638724 -0.01936914]
fit coeffs too far off [%] [-0.78362591 -0.1502459  -0.01853884]
 45%|████▌     | 571/1261 [01:21<01:37,  7.05it/s]
fit coeffs too far off [%] [-1.88142786  0.15170844 -0.03757366]
fit coeffs too far off [%] [-0.51882833 -0.7800722   0.05543739]
fit coeffs too far off [%] [-1.8507069   0.09547966 -0.03255923]
fit coeffs too far off [%] [-0.53790149 -0.78907124  0.05380954]
 45%|████▌     | 572/1261 [01:21<02:03,  5.57it/s]
fit coeffs too far off [%] [-2.03238028  0.01435407 -0.02289577]
fit coeffs too far off [%] [-0.68530567 -0.95043027  0.05646488]
fit coeffs too far off [%] [-0.68638388 -0.95062493  0.05434198]
fit coeffs too far off [%] [-3.03324728  0.63506189 -0.04452144]
fit coeffs too far off [%] [-0.72255427 -1.01374751  0.06245156]
 46%|████▌     | 575/1261 [01:21<01:44,  6.54it/s]
fit coeffs too far off [%] [-0.13645187 -0.88730485 -0.00513614]
fit coeffs too far off [%] [-2.08510192 -0.62114552  0.05995046]
fit coeffs too far off [%] [ -6.72630009e-02  -5.73884837e+00  -3.19766886e-03]
fit coeffs too far off [%] [-1.95553055 -0.62152188  0.05464309]
 46%|████▌     | 577/1261 [01:22<01:49,  6.27it/s]
fit coeffs too far off [%] [-2.66615481 -0.89677581  0.08637469]
fit coeffs too far off [%] [-0.21892051  4.19167428 -0.00831776]
fit coeffs too far off [%] [ 1.13007071 -6.11795783  0.05463822]
fit coeffs too far off [%] [-0.67415045 -1.85775317 -0.00760113]
 46%|████▌     | 579/1261 [01:22<01:35,  7.14it/s]
fit coeffs too far off [%] [ 0.39755141  0.92240025  0.04237748]
fit coeffs too far off [%] [ 3.50834129 -9.16334302 -0.02198905]
fit coeffs too far off [%] [-0.72591179 -0.83834328 -0.03726237]
fit coeffs too far off [%] [ 0.46133773  0.64253648 -0.01432129]
 46%|████▌     | 581/1261 [01:22<01:28,  7.69it/s]
fit coeffs too far off [%] [ 2.49494521  6.11163844  0.06613434]
fit coeffs too far off [%] [ 0.71556129  0.83462476 -0.01547845]
fit coeffs too far off [%] [ 0.89733401  0.99551525 -0.01665092]
 46%|████▌     | 582/1261 [01:22<01:41,  6.71it/s]
fit coeffs too far off [%] [-1.12044091 -1.35918783 -0.12647088]
fit coeffs too far off [%] [ 1.06613798  1.12795274 -0.01876174]
fit coeffs too far off [%] [-1.11439968 -1.33261034 -0.13358843]
fit coeffs too far off [%] [-1.61859131 -1.86758822 -0.17971946]
fit coeffs too far off [%] [-1.291851   -1.39548431  0.04591641]
 46%|████▋     | 585/1261 [01:23<01:36,  7.03it/s]
fit coeffs too far off [%] [ 1.47405162  1.07122283 -0.08732526]
fit coeffs too far off [%] [ 0.75893846  0.36939588 -0.00488591]
 46%|████▋     | 586/1261 [01:23<01:32,  7.32it/s]
fit coeffs too far off [%] [-1.47999582 -1.27352406  0.19290735]
fit coeffs too far off [%] [-1.65281551 -1.34629555  0.16704304]
 47%|████▋     | 588/1261 [01:23<01:37,  6.92it/s]
fit coeffs too far off [%] [-2.32968581 -1.48266377  0.11860483]
fit coeffs too far off [%] [-3.22638091 -1.61782462  0.10171433]
fit coeffs too far off [%] [-1.05465901 -0.42042126  0.01991311]
fit coeffs too far off [%] [ 0.83789506  0.76351052  0.01896195]
 47%|████▋     | 589/1261 [01:24<01:47,  6.23it/s]
fit coeffs too far off [%] [ 0.72229465  0.65327111  0.01701483]
fit coeffs too far off [%] [-26.33148319   1.80587254  -0.09302633]
 47%|████▋     | 592/1261 [01:24<01:37,  6.84it/s]
fit coeffs too far off [%] [ 1.09061712  0.49137794 -0.06854762]
fit coeffs too far off [%] [ 0.76618553  0.42363614 -0.06604872]
 47%|████▋     | 595/1261 [01:24<01:26,  7.67it/s]
fit coeffs too far off [%] [-2.81391397 -1.99339119  0.55473899]
fit coeffs too far off [%] [-2.77422554 -1.97090263  0.57345973]
fit coeffs too far off [%] [-3.62523499 -2.48050075  0.67846966]
fit coeffs too far off [%] [ 0.72629155  0.24318896  0.01162375]
 47%|████▋     | 596/1261 [01:25<01:39,  6.68it/s]
fit coeffs too far off [%] [-3.70014913 -2.50471656  0.67793764]
fit coeffs too far off [%] [ 0.87469093  0.28998188  0.0127348 ]
 47%|████▋     | 597/1261 [01:25<02:03,  5.36it/s]
fit coeffs too far off [%] [-1.33683224 -0.84722674  0.19534985]
fit coeffs too far off [%] [-1.00469849 -0.25705493  0.00493613]
fit coeffs too far off [%] [-1.00607842 -0.1529972   0.01050349]
fit coeffs too far off [%] [ 1.75088031 -2.58237962  0.08346222]
 48%|████▊     | 600/1261 [01:25<01:42,  6.43it/s]
fit coeffs too far off [%] [-0.33123916 -0.69768454 -0.02957825]
fit coeffs too far off [%] [-0.8321127  -3.06197576 -0.01912981]
 48%|████▊     | 601/1261 [01:25<01:36,  6.86it/s]
fit coeffs too far off [%] [ 3.53770191  0.14812508 -0.09625433]
fit coeffs too far off [%] [-1.52746625 -0.24308857  0.00905942]
fit coeffs too far off [%] [-1.50780342 -0.26049818  0.00772501]
fit coeffs too far off [%] [-0.66502862  0.90902469 -0.02949603]
fit coeffs too far off [%] [-2.50985218 -0.49097965  0.01212951]
 48%|████▊     | 602/1261 [01:26<01:45,  6.23it/s]
fit coeffs too far off [%] [-2.50615096 -0.47361895  0.01381525]
fit coeffs too far off [%] [ 1.05204156 -0.39564136  0.03531607]
fit coeffs too far off [%] [-1.92511335 -0.31702604  0.01724353]
 48%|████▊     | 605/1261 [01:26<01:36,  6.79it/s]
fit coeffs too far off [%] [-1.72034303  0.63332335  0.0048447 ]
fit coeffs too far off [%] [ 3.28499087 -4.93944262  0.16560687]
fit coeffs too far off [%] [  4.64030359e+00   7.17859628e-01   2.27770483e-04]
fit coeffs too far off [%] [ 3.00371985 -5.64785521  0.15743379]
 48%|████▊     | 607/1261 [01:26<01:38,  6.65it/s]
fit coeffs too far off [%] [ 4.16348431 -8.63413288  0.27824661]
 49%|████▉     | 617/1261 [01:28<01:21,  7.91it/s]
fit coeffs too far off [%] [-0.93321872 -0.32949845 -0.01115509]
fit coeffs too far off [%] [-0.93030733 -0.32520967 -0.01189232]
 64%|██████▍   | 806/1261 [01:51<00:57,  7.95it/s]
fit coeffs too far off [%] [ 0.78723421  0.08686134 -0.0095177 ]
fit coeffs too far off [%] [ 1.0354834   0.16545016 -0.00428967]
fit coeffs too far off [%] [ 0.78198346  0.13299491 -0.0044343 ]
 64%|██████▍   | 812/1261 [01:52<00:58,  7.72it/s]
fit coeffs too far off [%] [ 0.83450561  0.33645763  0.01409141]
fit coeffs too far off [%] [ 0.79106784  0.31975122  0.01315411]
 71%|███████   | 897/1261 [02:03<00:45,  8.05it/s]
fit coeffs too far off [%] [-1.00255561 -0.45233134 -0.03371637]
fit coeffs too far off [%] [-1.00257638 -0.45617564 -0.03773729]
fit coeffs too far off [%] [-0.99613131 -0.46580939 -0.03860178]
 71%|███████   | 898/1261 [02:03<00:53,  6.83it/s]
fit coeffs too far off [%] [-0.99597475 -0.45899544 -0.04016355]
 71%|███████▏  | 901/1261 [02:03<00:51,  6.98it/s]
fit coeffs too far off [%] [ 0.74779233  0.28893306  0.02574461]
fit coeffs too far off [%] [ 0.80846696  0.34342752  0.03073119]
fit coeffs too far off [%]
 72%|███████▏  | 903/1261 [02:04<00:53,  6.66it/s]
 [ 0.88259115  0.28795497  0.00976001]
 77%|███████▋  | 975/1261 [02:13<00:35,  8.05it/s]
fit coeffs too far off [%] [ 1.18322849  0.19280984  0.0061884 ]
fit coeffs too far off [%] [ 1.14582266  0.19167658  0.0058825 ]
 78%|███████▊  | 979/1261 [02:13<00:37,  7.55it/s]
fit coeffs too far off [%] [ 0.74628231  0.24402858  0.0199217 ]
fit coeffs too far off [%] [-1.5886194  -0.53076682 -0.0282588 ]
fit coeffs too far off [%] [-1.62579779 -0.52097188 -0.02694159]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-1.10668598 -0.41341068 -0.02388339]
fit coeffs too far off [%] [-1.08945323 -0.43524156 -0.02292248]
 78%|███████▊  | 981/1261 [02:14<01:09,  4.05it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-4.34374489 -1.73557139 -0.08614549]
 78%|███████▊  | 983/1261 [02:14<00:51,  5.40it/s]
fit coeffs too far off [%] [-0.99916016 -1.75212625  0.06578275]
fit coeffs too far off [%] [  6.01480184e+02  -1.39870992e+00  -4.52297594e-02]
 78%|███████▊  | 985/1261 [02:15<00:42,  6.45it/s]
fit coeffs too far off [%] [ 0.20244917  0.7289547  -0.00618069]
fit coeffs too far off [%] [-1.56424987 -3.57206973  0.07269133]
 78%|███████▊  | 988/1261 [02:15<00:37,  7.35it/s]
fit coeffs too far off [%] [ 0.80418286  0.63960171  0.04160523]
fit coeffs too far off [%] [ 0.74391992  0.62512604  0.04353381]
 79%|███████▉  | 1000/1261 [02:17<00:32,  8.01it/s]
fit coeffs too far off [%] [-0.71207991 -0.37485694 -0.01929709]
 79%|███████▉  | 1001/1261 [02:17<00:32,  8.05it/s]
fit coeffs too far off [%] [-1.40090975 -0.26442019  0.00215673]
fit coeffs too far off [%] [-1.47052423 -0.23002674  0.0036807 ]
 80%|███████▉  | 1003/1261 [02:17<00:36,  7.12it/s]
fit coeffs too far off [%] [-0.82303091 -1.16702835 -0.13805449]
fit coeffs too far off [%] [-0.8033321  -1.19154929 -0.12474046]
fit coeffs too far off [%] [-0.78475042 -1.58109391 -0.19253228]
 80%|███████▉  | 1004/1261 [02:17<00:40,  6.36it/s]
fit coeffs too far off [%] [-0.7930653  -1.61087026 -0.17619014]
fit coeffs too far off [%] [-0.38887088 -0.99942083 -0.1348229 ]
fit coeffs too far off [%] [ 4.23731407  0.27648897  0.01344529]
fit coeffs too far off [%] [ 4.86149891  0.27429176  0.01038084]
 80%|███████▉  | 1006/1261 [02:18<00:45,  5.64it/s]
fit coeffs too far off [%] [  4.13786028e-01   2.63752333e+03   2.56766644e-01]
fit coeffs too far off [%] [ 9.85422338  0.45670108 -0.01543879]
fit coeffs too far off [%] [ 11.78751751   0.45974121  -0.01878976]
fit coeffs too far off [%] [-1.39499264 -1.05912251 -0.08207541]
fit coeffs too far off [%] [ 8.06103797  0.29409945 -0.0167077 ]
 80%|████████  | 1009/1261 [02:18<00:38,  6.58it/s]
fit coeffs too far off [%] [ -3.50499892 -22.58153476   0.15869127]
 80%|████████  | 1012/1261 [02:18<00:33,  7.44it/s]
fit coeffs too far off [%] [-0.64021342 -0.78955576 -0.15111728]
fit coeffs too far off [%] [-0.65319029 -0.79108816 -0.14590601]
fit coeffs too far off [%] [-0.80949893 -0.9122842  -0.16555631]
 80%|████████  | 1013/1261 [02:19<00:38,  6.52it/s]
fit coeffs too far off [%] [-0.7987642  -0.90884114 -0.16289038]
fit coeffs too far off [%] [-0.96313736 -1.07616169 -0.18208384]
 81%|████████  | 1016/1261 [02:19<00:35,  6.84it/s]
fit coeffs too far off [%] [ 4.24423326 -0.66393468 -0.01589422]
fit coeffs too far off [%] [  2.73992354 -14.86839693   0.04026044]
 81%|████████  | 1018/1261 [02:19<00:32,  7.38it/s]
fit coeffs too far off [%] [ 0.57903477  1.0015447   0.04106882]
 81%|████████▏ | 1026/1261 [02:20<00:29,  7.88it/s]
fit coeffs too far off [%] [ 1.12358831  1.65244268  0.13477069]
fit coeffs too far off [%] [ 1.17998599  1.80375634  0.14475188]
fit coeffs too far off [%] [ 1.54925957  2.66113461  0.23580691]
 81%|████████▏ | 1027/1261 [02:21<00:34,  6.78it/s]
fit coeffs too far off [%] [ 1.58353916  2.83079472  0.24746746]
fit coeffs too far off [%] [ 1.63248541  3.1708706   0.30328067]
fit coeffs too far off [%] [ 0.79218364  0.13213392 -0.01255196]
 82%|████████▏ | 1028/1261 [02:21<00:37,  6.16it/s]
fit coeffs too far off [%] [ 0.71697057  0.1378236  -0.00840795]
fit coeffs too far off [%] [ 1.10381388  0.2507685  -0.00655572]
fit coeffs too far off [%] [ 1.15445189  0.27736205 -0.00274322]
 82%|████████▏ | 1031/1261 [02:21<00:37,  6.10it/s]
fit coeffs too far off [%] [  9.29880394e-01   2.28327456e-01  -6.95507409e-04]
 83%|████████▎ | 1049/1261 [02:24<00:26,  7.99it/s]
fit coeffs too far off [%] [-0.83688874 -0.14108035  0.00634784]
fit coeffs too far off [%] [-0.82232176 -0.13129467  0.0048106 ]
 84%|████████▍ | 1060/1261 [02:25<00:25,  7.88it/s]
fit coeffs too far off [%] [  7.96920406e-01   2.48643548e-01  -3.19139488e-04]
fit coeffs too far off [%] [  7.16844542e-01   2.31184051e-01   1.16929622e-04]
 88%|████████▊ | 1106/1261 [02:31<00:19,  7.88it/s]
fit coeffs too far off [%] [ 0.76996131  0.22857612  0.00666553]
fit coeffs too far off [%] [ 0.94586036  0.48532089  0.04399048]
fit coeffs too far off [%] [ 1.12459931  0.1290733  -0.00650308]
fit coeffs too far off [%] [ 0.80373421  0.45242157  0.04411721]
fit coeffs too far off [%] [ 0.96504371  0.10263567 -0.00871631]
 88%|████████▊ | 1107/1261 [02:31<00:26,  5.88it/s]
fit coeffs too far off [%] [ 0.86157587  0.12243737  0.00184224]
fit coeffs too far off [%] [ 0.81961011  0.12483159  0.00224906]
fit coeffs too far off [%] [ 1.73476406  0.26607347 -0.00175892]
 92%|█████████▏| 1161/1261 [02:38<00:12,  7.99it/s]
fit coeffs too far off [%] [ 0.92086483  0.73878454  0.07604308]
fit coeffs too far off [%] [ 1.06684503  0.7861846   0.07544351]
fit coeffs too far off [%] [ 0.94592377  0.64178878  0.05365206]
 97%|█████████▋| 1220/1261 [02:46<00:05,  7.80it/s]
fit coeffs too far off [%] [ 0.78736437  0.17281211  0.00612266]
fit coeffs too far off [%] [ 0.97463565  0.19626401  0.0063089 ]
fit coeffs too far off [%] [ 0.80301168  0.16481726  0.0099702 ]
 97%|█████████▋| 1221/1261 [02:46<00:05,  6.69it/s]
fit coeffs too far off [%] [ 1.04328723  0.17832754  0.00890786]
fit coeffs too far off [%] [ 1.41420881  0.2256988   0.00687536]
 98%|█████████▊| 1242/1261 [02:49<00:02,  7.86it/s]
fit coeffs too far off [%] [ 1.2593041   0.10731501 -0.00570646]
fit coeffs too far off [%] [ 1.17556028  0.11013698 -0.00488918]
 99%|█████████▊| 1243/1261 [02:49<00:02,  6.70it/s]
fit coeffs too far off [%] [ 1.20921483  0.15229367  0.00211937]
fit coeffs too far off [%] [ 1.0968237   0.16819537  0.00523275]
 99%|█████████▉| 1248/1261 [02:50<00:01,  7.35it/s]
fit coeffs too far off [%] [-1.42521834 -0.40144119 -0.02030527]
fit coeffs too far off [%] [-1.38418295 -0.39823218 -0.01796491]
fit coeffs too far off [%] [-1.22313353 -0.44434872 -0.02369584]
 99%|█████████▉| 1249/1261 [02:50<00:01,  6.44it/s]
fit coeffs too far off [%] [-1.21844178 -0.4197525  -0.01728297]
 99%|█████████▉| 1253/1261 [02:50<00:01,  7.11it/s]
fit coeffs too far off [%] [  7.05374651e+00   6.45853120e-01   1.99674395e-03]
fit coeffs too far off [%] [  6.79256123e+00   6.15863065e-01   1.38050295e-04]
 99%|█████████▉| 1254/1261 [02:50<00:01,  6.31it/s]
fit coeffs too far off [%] [  2.67731937e+00   2.90899548e-01   6.72245279e-04]
fit coeffs too far off [%] [  2.05452799e+00   2.79080880e-01   1.80786364e-03]
fit coeffs too far off [%] [-1.11637013 -0.35314094 -0.0200271 ]
100%|█████████▉| 1257/1261 [02:51<00:00,  6.70it/s]
fit coeffs too far off [%] [-0.07950971 -0.51810921 -0.02234786]
fit coeffs too far off [%] [ -1.46097267e+01   3.79602879e-01   1.10817341e-03]
fit coeffs too far off [%] [-0.2320774  -0.86351122 -0.02673564]
fit coeffs too far off [%] [-0.21637989 -0.85898471 -0.0260451 ]
100%|█████████▉| 1258/1261 [02:51<00:00,  6.06it/s]
fit coeffs too far off [%] [-0.66818806 -1.51833248 -0.02981913]
fit coeffs too far off [%] [ 1.57026674  0.48025717  0.00196017]
fit coeffs too far off [%] [-0.66744051 -1.56651803 -0.02693648]
fit coeffs too far off [%] [ 1.76708265  0.53603813  0.00399783]
100%|█████████▉| 1260/1261 [02:52<00:00,  5.69it/s]
fit coeffs too far off [%] [-1.11622935 -3.88230346 -0.05056135]
fit coeffs too far off [%] [ 1.99003755  0.65610731  0.00937955]
fit coeffs too far off [%] [ 1.78416696  0.42032777 -0.02122303]
fit coeffs too far off [%] [-1.21643898 -0.64393692 -0.01619572]

[MoviePy] Done.
[MoviePy] >>>> Video ready: ./output_images/test_results/detected_lane_project_video.mp4 

CPU times: user 5min 52s, sys: 9.62 s, total: 6min 1s
Wall time: 2min 52s
In [21]:
HTML("""
<video width="960" height="540" controls>
  <source src="{0}">
</video>
""".format(output))
Out[21]:
In [22]:
output2 = out_dir+'detected_lane_challenge_video.mp4'
clip2 = VideoFileClip("challenge_video.mp4")
out_clip2 = clip2.fl_image(process_image) 
%time out_clip2.write_videofile(output2, audio=False)
fit coeffs too far off [%] [ 58.50380669   4.24493418   0.36332203]
fit coeffs too far off [%] [-15.58371784   6.86780574   0.0367952 ]
[MoviePy] >>>> Building video ./output_images/test_results/detected_lane_challenge_video.mp4
[MoviePy] Writing video ./output_images/test_results/detected_lane_challenge_video.mp4
  0%|          | 2/485 [00:00<01:05,  7.37it/s]
fit coeffs too far off [%] [ 0.84917943  2.13746851 -0.26092799]
fit coeffs too far off [%] [ 0.84917943  2.13746851 -0.26092799]
Trouble ahead! 3 lanes detected!
  1%|          | 4/485 [00:00<01:24,  5.69it/s]
fit coeffs too far off [%] [ -6.07703293 -12.67056895   0.79277692]
fit coeffs too far off [%] [-1.20241999 -1.11324276 -0.48869306]
  1%|▏         | 7/485 [00:01<01:06,  7.19it/s]
fit coeffs too far off [%] [ 0.45177346  0.77277667 -0.15303523]
fit coeffs too far off [%] [ 0.42966085  0.7053508  -0.14463119]
Trouble ahead! 3 lanes detected!
  2%|▏         | 8/485 [00:01<01:36,  4.97it/s]
fit coeffs too far off [%] [ -7.80910831 -11.34011052   1.86454998]
fit coeffs too far off [%] [ -7.63873299 -10.54152501   1.95991087]
Trouble ahead! 3 lanes detected!
  2%|▏         | 10/485 [00:01<01:38,  4.82it/s]
fit coeffs too far off [%] [ -7.47879574 -10.39442277   1.95019162]
fit coeffs too far off [%] [-0.97845621 -0.9756843  -0.62511507]
  2%|▏         | 12/485 [00:02<01:17,  6.12it/s]
fit coeffs too far off [%] [ 13.06506894  10.53099776   0.41612987]
fit coeffs too far off [%] [-1.52162729 -1.44044591 -0.41217482]
  3%|▎         | 14/485 [00:02<01:06,  7.08it/s]
fit coeffs too far off [%] [-2.1928287  -2.29895349  0.37095777]
fit coeffs too far off [%] [-0.96743425 -0.88486702 -0.09588994]
  3%|▎         | 16/485 [00:02<01:00,  7.70it/s]
fit coeffs too far off [%] [ 3.2942279   0.45367341 -0.02784765]
  4%|▎         | 17/485 [00:02<00:59,  7.83it/s]
fit coeffs too far off [%] [ 2.99744549  3.26013909  0.1454133 ]
fit coeffs too far off [%] [ 3.80762856  4.28482058  0.15607197]
Trouble ahead! 3 lanes detected!
  4%|▍         | 19/485 [00:03<01:19,  5.86it/s]
fit coeffs too far off [%] [-7.82266621 -8.239882   -0.27114336]
  4%|▍         | 20/485 [00:03<01:12,  6.45it/s]
fit coeffs too far off [%] [ 0.77172465  0.77436158 -0.33006166]
fit coeffs too far off [%] [ 0.72703584  0.67492218 -0.29977358]
Trouble ahead! 3 lanes detected!
  5%|▍         | 23/485 [00:03<01:15,  6.10it/s]
fit coeffs too far off [%] [-3.54152651 -2.57504759  0.83541828]
fit coeffs too far off [%] [-3.89569468 -2.67669037  0.82364731]
Trouble ahead! 3 lanes detected!
  5%|▍         | 24/485 [00:04<01:40,  4.59it/s]
fit coeffs too far off [%] [-8.85648741 -7.86335112  2.60800875]
fit coeffs too far off [%] [-8.83985584 -7.75591687  2.65944887]
Trouble ahead! 3 lanes detected!
  5%|▌         | 26/485 [00:04<01:38,  4.68it/s]
fit coeffs too far off [%] [-14.34609842 -10.27352656   3.18038327]
fit coeffs too far off [%] [-0.83890731 -0.89429583 -0.63192799]
  6%|▌         | 27/485 [00:04<01:25,  5.38it/s]
fit coeffs too far off [%] [-2.42755332 -3.21302529 -0.49901184]
fit coeffs too far off [%] [-1.19491763 -1.17313666 -0.22317711]
fit coeffs too far off [%] [-1.20595908 -1.18106098 -0.21822929]
Trouble ahead! 3 lanes detected!
  6%|▌         | 29/485 [00:05<01:30,  5.05it/s]
fit coeffs too far off [%] [-2.13342261 -1.93882203  1.56627751]
fit coeffs too far off [%] [ 0.541782    0.72246366  0.31647278]
  6%|▋         | 31/485 [00:05<01:11,  6.33it/s]
fit coeffs too far off [%] [-0.66880259 -0.64164849 -0.24254723]
  7%|▋         | 33/485 [00:05<01:02,  7.25it/s]
fit coeffs too far off [%] [-0.98330952 -0.99254147 -0.22329496]
fit coeffs too far off [%] [-0.9831532  -0.99250133 -0.22358049]
Trouble ahead! 3 lanes detected!
  7%|▋         | 34/485 [00:06<01:29,  5.01it/s]
fit coeffs too far off [%] [ 0.86386043  0.84064764  0.22871987]
fit coeffs too far off [%] [ 0.773233    0.76472135  0.2185018 ]
Trouble ahead! 3 lanes detected!
  7%|▋         | 35/485 [00:06<01:48,  4.13it/s]
lane too far away
fit coeffs too far off [%] [ 0.35678727  1.28128762  0.46767765]
lane too far away
fit coeffs too far off [%] [ 0.30400553  1.17354656  0.44214529]
Trouble ahead! 3 lanes detected!
  7%|▋         | 36/485 [00:06<02:02,  3.66it/s]
lane too far away
fit coeffs too far off [%] [-0.25381851  0.66467975  0.30204524]
lane too far away
Trouble ahead! 3 lanes detected!
  8%|▊         | 38/485 [00:07<01:47,  4.16it/s]
fit coeffs too far off [%] [-0.61362597 -0.60067167 -0.32903272]
fit coeffs too far off [%] [-0.61362597 -0.60067167 -0.32903272]
Trouble ahead! 3 lanes detected!
  8%|▊         | 39/485 [00:07<02:00,  3.69it/s]
fit coeffs too far off [%] [-1.47173503 -1.48081521 -0.36844041]
fit coeffs too far off [%] [-1.44994824 -1.4613999  -0.37279686]
fit coeffs too far off [%] [-0.54254793 -0.53238968 -0.27644177]
fit coeffs too far off [%] [-0.54254793 -0.53238968 -0.27644177]
  8%|▊         | 41/485 [00:07<01:41,  4.38it/s]
fit coeffs too far off [%] [-1.48333409 -1.51144906 -0.37812206]
fit coeffs too far off [%] [-1.53061104 -1.55129174 -0.37084882]
fit coeffs too far off [%] [-0.63807073 -0.62359915 -0.34537764]
fit coeffs too far off [%] [-1.52490099 -1.52505873 -0.36672843]
fit coeffs too far off [%] [-0.63807073 -0.62359915 -0.34537764]
fit coeffs too far off [%] [-1.50306873 -1.50187097 -0.37452563]
  9%|▉         | 44/485 [00:08<01:27,  5.06it/s]
fit coeffs too far off [%] [-1.52528414 -1.52819609 -0.38336567]
fit coeffs too far off [%] [-0.58093996 -0.58304571 -0.33304124]
fit coeffs too far off [%] [-3.47583204 -3.43007314  0.7252238 ]
fit coeffs too far off [%] [-0.58093996 -0.58304571 -0.33304124]
Trouble ahead! 3 lanes detected!
  9%|▉         | 46/485 [00:09<01:29,  4.90it/s]
fit coeffs too far off [%] [-0.61214585 -0.6265208  -0.3760984 ]
fit coeffs too far off [%] [-0.61214585 -0.6265208  -0.3760984 ]
Trouble ahead! 3 lanes detected!
 10%|▉         | 48/485 [00:09<01:31,  4.79it/s]
fit coeffs too far off [%] [-0.60897768 -0.61817341 -0.36308106]
fit coeffs too far off [%] [-0.60897768 -0.61817341 -0.36308106]
 10%|█         | 50/485 [00:09<01:18,  5.57it/s]
fit coeffs too far off [%] [-0.56318262 -0.57665912 -0.35372877]
fit coeffs too far off [%] [-1.6883869  -1.83514158 -0.37071882]
fit coeffs too far off [%] [-0.56318262 -0.57665912 -0.35372877]
fit coeffs too far off [%] [-1.74142588 -1.88514222 -0.36772565]
Trouble ahead! 3 lanes detected!
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-1.25714515 -1.59080866 -0.34156287]
fit coeffs too far off [%] [-1.24803622 -1.58762958 -0.34106718]
 11%|█         | 52/485 [00:10<01:54,  3.77it/s]
fit coeffs too far off [%] [-0.52226975 -0.55593365 -0.37933887]
fit coeffs too far off [%] [-0.52226975 -0.55593365 -0.37933887]
Trouble ahead! 3 lanes detected!
 11%|█         | 54/485 [00:11<01:43,  4.18it/s]
fit coeffs too far off [%] [-0.47643418 -0.54711549 -0.41879918]
fit coeffs too far off [%] [-0.47643418 -0.54711549 -0.41879918]
Trouble ahead! 4 lanes detected!
 11%|█▏        | 55/485 [00:11<01:57,  3.67it/s]
fit coeffs too far off [%] [-0.8567407  -0.79448672 -0.07644697]
fit coeffs too far off [%] [-0.85968709 -0.79994051 -0.07773208]
Trouble ahead! 3 lanes detected!
 12%|█▏        | 56/485 [00:11<02:06,  3.39it/s]
fit coeffs too far off [%] [-0.64155928 -0.65942827 -0.35295231]
fit coeffs too far off [%] [-2.19381693 -2.11575142 -0.33701416]
fit coeffs too far off [%] [-0.64155928 -0.65942827 -0.35295231]
fit coeffs too far off [%] [-2.2853245  -2.17567246 -0.33603962]
Trouble ahead! 3 lanes detected!
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-2.37757632 -2.16544456 -0.32632216]
 12%|█▏        | 58/485 [00:12<02:09,  3.30it/s]
fit coeffs too far off [%] [-0.80171286 -0.80976978 -0.39585353]
fit coeffs too far off [%] [-0.80171286 -0.80976978 -0.39585353]
Trouble ahead! 3 lanes detected!
 12%|█▏        | 60/485 [00:12<01:49,  3.89it/s]
fit coeffs too far off [%] [-0.50796241 -0.54663155 -0.29404259]
fit coeffs too far off [%] [-0.50796241 -0.54663155 -0.29404259]
Trouble ahead! 3 lanes detected!
 13%|█▎        | 62/485 [00:13<01:39,  4.27it/s]
fit coeffs too far off [%] [-0.42378064 -0.50634245 -0.28921571]
fit coeffs too far off [%] [-0.42378064 -0.50634245 -0.28921571]
Trouble ahead! 3 lanes detected!
 13%|█▎        | 64/485 [00:13<01:34,  4.46it/s]
fit coeffs too far off [%] [-0.42360268 -0.49222368 -0.27144247]
fit coeffs too far off [%] [-0.85220598 -0.74641534  0.05985865]
fit coeffs too far off [%] [-0.42360268 -0.49222368 -0.27144247]
fit coeffs too far off [%] [-0.86405311 -0.76049038  0.05757174]
Trouble ahead! 3 lanes detected!
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.01597168 -0.30294535  0.16985023]
fit coeffs too far off [%] [-0.0181616  -0.29099881  0.16818159]
 14%|█▎        | 66/485 [00:14<02:19,  3.01it/s]
Trouble ahead! 3 lanes detected!
 14%|█▍        | 67/485 [00:14<01:52,  3.72it/s]
fit coeffs too far off [%] [-0.58861043 -0.57486634 -0.13137065]
fit coeffs too far off [%] [-0.60006859 -0.57918462 -0.13562607]
Trouble ahead! 3 lanes detected!
 14%|█▍        | 68/485 [00:15<02:01,  3.44it/s]
fit coeffs too far off [%] [ 0.60639963  0.76350295  0.39770645]
fit coeffs too far off [%] [-1.10522014 -0.81911286 -0.06053433]
fit coeffs too far off [%] [ 0.60639963  0.76350295  0.39770645]
fit coeffs too far off [%] [-1.1082492  -0.81296854 -0.07875612]
Trouble ahead! 3 lanes detected!
Trouble ahead! 3 lanes detected!
 14%|█▍        | 70/485 [00:15<02:05,  3.31it/s]
fit coeffs too far off [%] [-0.62916353 -0.66835393 -0.37512779]
fit coeffs too far off [%] [-0.59767134 -0.55408637  0.04273007]
fit coeffs too far off [%] [-0.62916353 -0.66835393 -0.37512779]
fit coeffs too far off [%] [-0.63529967 -0.58860015  0.06007544]
 15%|█▍        | 72/485 [00:16<01:38,  4.18it/s]
fit coeffs too far off [%] [-0.49672083 -0.57129208 -0.34489692]
fit coeffs too far off [%] [-1.51753883 -1.20550123  0.01593851]
fit coeffs too far off [%] [-0.49672083 -0.57129208 -0.34489692]
fit coeffs too far off [%] [-1.51496488 -1.20148209  0.02444303]
Trouble ahead! 3 lanes detected!
 15%|█▌        | 73/485 [00:16<02:17,  2.99it/s]
Trouble ahead! 3 lanes detected!
 15%|█▌        | 74/485 [00:16<01:51,  3.69it/s]
fit coeffs too far off [%] [-1.58836769 -1.28084252  0.01729851]
fit coeffs too far off [%] [-1.56526835 -1.27309697  0.01918006]
Trouble ahead! 3 lanes detected!
 15%|█▌        | 75/485 [00:17<01:59,  3.42it/s]
fit coeffs too far off [%] [-0.4994706  -0.47399599 -0.27246418]
fit coeffs too far off [%] [-0.49478987 -0.46677773 -0.26452768]
Trouble ahead! 3 lanes detected!
 16%|█▌        | 76/485 [00:17<02:05,  3.26it/s]
fit coeffs too far off [%] [-1.76887392 -1.44685282 -0.00545681]
fit coeffs too far off [%] [-1.77242144 -1.45415917 -0.01729436]
Trouble ahead! 3 lanes detected!
 16%|█▌        | 77/485 [00:17<02:09,  3.16it/s]
fit coeffs too far off [%] [-0.35894473 -0.43085833 -0.24400894]
fit coeffs too far off [%] [-0.36755463 -0.4318189  -0.2417189 ]
Trouble ahead! 3 lanes detected!
 16%|█▌        | 78/485 [00:18<02:11,  3.09it/s]
fit coeffs too far off [%] [-0.48436607 -0.42736831 -0.21984444]
fit coeffs too far off [%] [-2.08832342 -1.73732816 -0.00684895]
fit coeffs too far off [%] [-0.48436607 -0.42736831 -0.21984444]
fit coeffs too far off [%] [-2.09368603 -1.74739152 -0.01170689]
Trouble ahead! 3 lanes detected!
 16%|█▋        | 79/485 [00:18<02:39,  2.55it/s]
Trouble ahead! 3 lanes detected!
 16%|█▋        | 80/485 [00:18<02:06,  3.21it/s]
fit coeffs too far off [%] [-0.27473819 -0.39673282 -0.23010917]
fit coeffs too far off [%] [-1.81464111 -1.45079457 -0.01725946]
fit coeffs too far off [%] [-0.27473819 -0.39673282 -0.23010917]
fit coeffs too far off [%] [-1.82621502 -1.45711494 -0.01702232]
Trouble ahead! 3 lanes detected!
 17%|█▋        | 81/485 [00:19<02:35,  2.61it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-1.53019441 -2.05105675  0.55678793]
fit coeffs too far off [%] [-1.58859708 -2.13472743  0.55507544]
 17%|█▋        | 82/485 [00:19<02:29,  2.70it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.95207474 -1.43000537  0.42931341]
 17%|█▋        | 84/485 [00:20<01:37,  4.11it/s]
fit coeffs too far off [%] [ 12.73646838  -2.88935707  -0.33340956]
 18%|█▊        | 87/485 [00:20<01:05,  6.10it/s]
fit coeffs too far off [%] [ 0.78394668  0.51583555 -0.02109236]
fit coeffs too far off [%] [ 0.70407541  0.46833676 -0.02176725]
Trouble ahead! 3 lanes detected!
 18%|█▊        | 88/485 [00:20<01:25,  4.64it/s]
fit coeffs too far off [%] [-1.46070896 -1.87752148  0.49431122]
fit coeffs too far off [%] [-1.4724666  -1.87177128  0.50866966]
Trouble ahead! 3 lanes detected!
 19%|█▊        | 90/485 [00:21<01:24,  4.69it/s]
fit coeffs too far off [%] [-0.83293869 -1.2027149   0.35394169]
fit coeffs too far off [%] [ 0.7267539   0.37258684  0.13918976]
fit coeffs too far off [%] [ 7.5402629  -7.20331651 -0.2833798 ]
fit coeffs too far off [%] [ 0.7013043   0.36363948  0.13543276]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.91003193 -0.78452059  0.11675491]
 19%|█▉        | 93/485 [00:21<01:12,  5.39it/s]
fit coeffs too far off [%] [ 17.7753542    5.79789134  -0.13123373]
fit coeffs too far off [%] [-0.84455863 -0.46340882 -0.16493862]
fit coeffs too far off [%] [-1.07852612 -1.0461059   0.12383967]
fit coeffs too far off [%] [-0.84633541 -0.45064844 -0.14759181]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 19.38494322  33.13184248   0.41480041]
 20%|█▉        | 96/485 [00:22<01:09,  5.61it/s]
fit coeffs too far off [%] [-0.82523965 -0.40118819 -0.12905618]
fit coeffs too far off [%] [-0.83367606 -0.41046461 -0.13038777]
Trouble ahead! 3 lanes detected!
 20%|██        | 97/485 [00:22<01:27,  4.45it/s]
fit coeffs too far off [%] [ 2.73702801  1.14338061  0.34619284]
fit coeffs too far off [%] [ 2.71733085  1.11617542  0.33393045]
Trouble ahead! 3 lanes detected!
 20%|██        | 98/485 [00:23<01:39,  3.89it/s]
fit coeffs too far off [%] [ 5.68411663  2.33202761  0.68139235]
fit coeffs too far off [%] [ 0.80795319  0.55113392  0.04825986]
fit coeffs too far off [%] [ 0.74679139  0.5014138   0.04096434]
Trouble ahead! 3 lanes detected!
 20%|██        | 99/485 [00:23<01:47,  3.58it/s]
fit coeffs too far off [%] [ 2.20546427  1.66052093  0.27056596]
fit coeffs too far off [%] [ 5.18928212  2.81405689  0.3178374 ]
Trouble ahead! 3 lanes detected!
 21%|██        | 100/485 [00:23<01:54,  3.36it/s]
fit coeffs too far off [%] [-0.7025108  -0.73283509 -0.26948519]
fit coeffs too far off [%] [ 1.29127355  0.585625    0.02878325]
fit coeffs too far off [%] [-0.72035546 -0.7367355  -0.26451526]
Trouble ahead! 3 lanes detected!
 21%|██        | 102/485 [00:24<01:36,  3.97it/s]
fit coeffs too far off [%] [-0.73150146 -0.55538609 -0.27654989]
 22%|██▏       | 105/485 [00:24<01:02,  6.04it/s]
fit coeffs too far off [%] [-0.76651026 -0.62544649 -0.10746297]
fit coeffs too far off [%] [-0.76425242 -0.62262203 -0.10786022]
Trouble ahead! 3 lanes detected!
 22%|██▏       | 106/485 [00:24<01:21,  4.64it/s]
fit coeffs too far off [%] [-1.33509232 -1.05945483 -0.18546859]
fit coeffs too far off [%] [-1.34681372 -1.06198084 -0.17789411]
Trouble ahead! 3 lanes detected!
 22%|██▏       | 108/485 [00:25<01:21,  4.64it/s]
fit coeffs too far off [%] [ 3.16169674  2.05434665  0.26538067]
fit coeffs too far off [%] [ 5.24211844  2.75418299  0.28266297]
Trouble ahead! 3 lanes detected!
 23%|██▎       | 110/485 [00:25<01:19,  4.73it/s]
fit coeffs too far off [%] [-1.31822655 -0.75751096 -0.09737249]
fit coeffs too far off [%] [ 1.23168573  0.8058215   0.3408959 ]
fit coeffs too far off [%] [-3.37559654  1.05842784 -0.07219646]
fit coeffs too far off [%] [ 1.37294811  0.86507439  0.35413773]
 23%|██▎       | 111/485 [00:26<01:33,  4.01it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 1.53637068  1.01463421  0.43664835]
fit coeffs too far off [%] [-2.37203258 -1.56274218 -0.02466373]
fit coeffs too far off [%] [ 1.2414825   0.86614778  0.392343  ]
 23%|██▎       | 112/485 [00:26<01:42,  3.65it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 1.67765627  1.17453423  0.52879195]
 24%|██▍       | 118/485 [00:27<00:50,  7.22it/s]
fit coeffs too far off [%] [ 0.4022603  0.3625716  0.2583149]
fit coeffs too far off [%] [ 0.37092734  0.33673908  0.24233278]
Trouble ahead! 3 lanes detected!
 25%|██▍       | 119/485 [00:27<01:12,  5.05it/s]
fit coeffs too far off [%] [ 0.35801937  0.33940682  0.26090145]
fit coeffs too far off [%] [-0.21013271 -0.51961367  0.04000594]
fit coeffs too far off [%] [ 0.2652161   0.25516663  0.20283553]
fit coeffs too far off [%] [-0.18581903 -0.52198709  0.045316  ]
Trouble ahead! 3 lanes detected!
 25%|██▍       | 120/485 [00:28<01:50,  3.29it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.3055538   0.32198313  0.27609402]
fit coeffs too far off [%] [ 4.90853098  3.39404056 -0.03084963]
fit coeffs too far off [%] [ 5.24869998  3.37130609 -0.02397974]
 25%|██▍       | 121/485 [00:28<01:53,  3.21it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.58952242 -0.55853467 -0.4277281 ]
fit coeffs too far off [%] [ 2.73222386  1.75210051 -0.01434014]
 25%|██▌       | 123/485 [00:28<01:17,  4.65it/s]
fit coeffs too far off [%] [ 1.64294257  1.64505865 -0.17140834]
fit coeffs too far off [%] [-1.12427938 -1.23531907 -0.12218018]
 26%|██▌       | 125/485 [00:28<01:00,  5.98it/s]
fit coeffs too far off [%] [ 1.50805588  1.1040052   0.0421006 ]
fit coeffs too far off [%] [-1.24154523 -1.07197377 -0.62270386]
fit coeffs too far off [%] [-1.25275664 -1.07442894 -0.61691358]
 26%|██▌       | 126/485 [00:29<01:02,  5.72it/s]
fit coeffs too far off [%] [-0.63489253 -0.65299    -0.43948711]
fit coeffs too far off [%] [-0.60808764 -0.63594256 -0.42885574]
fit coeffs too far off [%] [-0.5889534  -0.62351409 -0.42297611]
 28%|██▊       | 135/485 [00:30<00:43,  7.97it/s]
fit coeffs too far off [%] [-0.67357699 -1.13088099 -0.89104585]
fit coeffs too far off [%] [-0.67357699 -1.13088099 -0.89104585]
fit coeffs too far off [%] [-0.64389813 -1.1318715  -0.89148651]
fit coeffs too far off [%] [-0.64389813 -1.1318715  -0.89148651]
Trouble ahead! 1 lanes detected!
 28%|██▊       | 136/485 [00:30<01:28,  3.95it/s]
Trouble ahead! 1 lanes detected!
fit coeffs too far off [%] [-4.92368316 -2.29207813 -0.11923207]
fit coeffs too far off [%] [-4.92368316 -2.29207813 -0.11923207]
fit coeffs too far off [%] [-6.58943675 -2.35169574 -0.1143948 ]
fit coeffs too far off [%] [-6.58943675 -2.35169574 -0.1143948 ]
Trouble ahead! 1 lanes detected!
Trouble ahead! 1 lanes detected!
fit coeffs too far off [%] [-6.74930206 -2.33587435 -0.10114294]
fit coeffs too far off [%] [-6.74930206 -2.33587435 -0.10114294]
 29%|██▊       | 139/485 [00:31<01:20,  4.32it/s]
fit coeffs too far off [%] [-2.3479113  -2.2694961   0.14917885]
fit coeffs too far off [%] [-2.3479113  -2.2694961   0.14917885]
fit coeffs too far off [%] [-1.81697735 -1.72939703 -0.03091742]
fit coeffs too far off [%] [-1.81697735 -1.72939703 -0.03091742]
 29%|██▉       | 141/485 [00:31<01:00,  5.68it/s]
fit coeffs too far off [%] [-1.16025105 -1.7918089   0.00851867]
fit coeffs too far off [%] [-1.16025105 -1.7918089   0.00851867]
fit coeffs too far off [%] [-0.93277212 -0.1061649   0.00494338]
fit coeffs too far off [%] [-0.93277212 -0.1061649   0.00494338]
 29%|██▉       | 143/485 [00:32<00:50,  6.78it/s]
fit coeffs too far off [%] [-1116.06218577   -40.28511435   -12.88445525]
fit coeffs too far off [%] [-1116.06218577   -40.28511435   -12.88445525]
lane too far away
fit coeffs too far off [%] [ 1.35565322  1.30684226  1.30739006]
lane too far away
fit coeffs too far off [%] [ 1.35565322  1.30684226  1.30739006]
lane too far away
lane too far away
Trouble ahead! 3 lanes detected!
 30%|██▉       | 144/485 [00:32<01:32,  3.70it/s]
Trouble ahead! 3 lanes detected!
 30%|██▉       | 145/485 [00:32<01:16,  4.43it/s]
fit coeffs too far off [%] [-4.54928789 -0.71647492 -0.15543876]
fit coeffs too far off [%] [-2.29023788 -1.64004125 -0.04691959]
fit coeffs too far off [%] [-4.54928789 -0.71647492 -0.15543876]
fit coeffs too far off [%] [-2.29023788 -1.64004125 -0.04691959]
Trouble ahead! 3 lanes detected!
 30%|███       | 146/485 [00:33<01:49,  3.10it/s]
Trouble ahead! 3 lanes detected!
 30%|███       | 147/485 [00:33<01:28,  3.81it/s]
fit coeffs too far off [%] [-0.88402636 -0.08060268 -0.01207453]
fit coeffs too far off [%] [-10.82928538   5.16019918   0.06988354]
fit coeffs too far off [%] [-0.88402636 -0.08060268 -0.01207453]
fit coeffs too far off [%] [-10.82928538   5.16019918   0.06988354]
Trouble ahead! 3 lanes detected!
 31%|███       | 148/485 [00:34<01:58,  2.85it/s]
Trouble ahead! 3 lanes detected!
 31%|███       | 149/485 [00:34<01:35,  3.54it/s]
fit coeffs too far off [%] [ 3.48124723  0.27697339  0.0767915 ]
fit coeffs too far off [%] [ 9.18591046  2.91385989  0.07072197]
fit coeffs too far off [%] [ 3.48124723  0.27697339  0.0767915 ]
fit coeffs too far off [%] [ 9.18591046  2.91385989  0.07072197]
Trouble ahead! 3 lanes detected!
 31%|███       | 150/485 [00:34<02:02,  2.73it/s]
Trouble ahead! 3 lanes detected!
 31%|███       | 151/485 [00:34<01:38,  3.39it/s]
fit coeffs too far off [%] [-2.61481981 -0.08819419  0.01231539]
fit coeffs too far off [%] [-2.61481981 -0.08819419  0.01231539]
Trouble ahead! 3 lanes detected!
 31%|███▏      | 152/485 [00:35<01:43,  3.23it/s]
fit coeffs too far off [%] [-1.7140843  -1.67363345 -0.10242929]
fit coeffs too far off [%] [-1.82577721 -1.70633739 -0.10980378]
Trouble ahead! 3 lanes detected!
 32%|███▏      | 153/485 [00:35<01:46,  3.13it/s]
fit coeffs too far off [%] [ 2.69423368  1.58855063  0.04394158]
fit coeffs too far off [%] [ 2.69423368  1.58855063  0.04394158]
Trouble ahead! 3 lanes detected!
 32%|███▏      | 154/485 [00:35<01:52,  2.95it/s]
fit coeffs too far off [%] [-0.78054363 -0.08527627 -0.01175186]
fit coeffs too far off [%] [-0.74848807 -0.07803961 -0.01297751]
Trouble ahead! 3 lanes detected!
 32%|███▏      | 155/485 [00:36<01:52,  2.93it/s]
fit coeffs too far off [%] [ 2.3539616   0.07500205 -0.0199751 ]
fit coeffs too far off [%] [ 2.3539616   0.07500205 -0.0199751 ]
Trouble ahead! 3 lanes detected!
 33%|███▎      | 158/485 [00:36<01:15,  4.33it/s]
fit coeffs too far off [%] [-2.4393128  -2.60680033  0.27920084]
fit coeffs too far off [%] [-2.64200048 -2.77727118  0.27431774]
 33%|███▎      | 159/485 [00:37<01:28,  3.69it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-2.51849144 -2.74132252  0.2620219 ]
fit coeffs too far off [%] [-2.92029008 -3.27892967  0.23152524]
 33%|███▎      | 160/485 [00:37<01:34,  3.44it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-1.02165245 -0.76160757  0.01324101]
 33%|███▎      | 162/485 [00:37<01:06,  4.84it/s]
fit coeffs too far off [%] [ 166.15334303  -15.87304232    0.27856736]
lane too far away
lane too far away
 34%|███▎      | 163/485 [00:38<01:19,  4.05it/s]
Trouble ahead! 3 lanes detected!
 34%|███▍      | 164/485 [00:38<01:07,  4.77it/s]
lane too far away
lane too far away
Trouble ahead! 3 lanes detected!
 34%|███▍      | 167/485 [00:38<00:58,  5.41it/s]
fit coeffs too far off [%] [ 1.69118959  0.95783632  0.04044446]
fit coeffs too far off [%] [ 1.61638698  0.90257781  0.03624096]
Trouble ahead! 3 lanes detected!
 35%|███▌      | 170/485 [00:39<00:55,  5.67it/s]
fit coeffs too far off [%] [ 2.82606066  1.69673294  0.09234589]
fit coeffs too far off [%] [ 3.20212661  1.87516284  0.09961176]
Trouble ahead! 3 lanes detected!
 35%|███▌      | 171/485 [00:39<01:10,  4.43it/s]
fit coeffs too far off [%] [-2.96156092 -2.92345956 -0.41080745]
fit coeffs too far off [%] [-3.03080687 -2.95088299 -0.41060748]
Trouble ahead! 3 lanes detected!
 36%|███▌      | 173/485 [00:40<01:08,  4.57it/s]
fit coeffs too far off [%] [ 1.25571739  0.70527974  0.03791837]
 37%|███▋      | 179/485 [00:41<00:40,  7.47it/s]
fit coeffs too far off [%] [-1.09135266 -0.741257   -0.03558282]
fit coeffs too far off [%] [-1.0969033  -0.72800833 -0.03031204]
Trouble ahead! 3 lanes detected!
 37%|███▋      | 180/485 [00:41<00:59,  5.12it/s]
fit coeffs too far off [%] [-0.94308355 -0.59613513 -0.02288373]
fit coeffs too far off [%] [-0.92978278 -0.55011731 -0.02170334]
Trouble ahead! 3 lanes detected!
 38%|███▊      | 182/485 [00:41<01:01,  4.91it/s]
fit coeffs too far off [%] [-2.09442751 -1.6432494  -0.14890763]
fit coeffs too far off [%] [-2.0919403  -2.92226607  0.21194794]
 39%|███▉      | 188/485 [00:42<00:38,  7.66it/s]
fit coeffs too far off [%] [-0.6416637  -0.57791103 -0.07253051]
fit coeffs too far off [%] [-0.61210781 -0.55364641 -0.07107335]
Trouble ahead! 3 lanes detected!
 39%|███▉      | 189/485 [00:42<00:57,  5.19it/s]
fit coeffs too far off [%] [ 0.96467687  0.71511272  0.2689703 ]
fit coeffs too far off [%] [ 0.96962961  0.7103493   0.26490185]
Trouble ahead! 3 lanes detected!
 39%|███▉      | 190/485 [00:43<01:09,  4.26it/s]
fit coeffs too far off [%] [-0.85729557 -0.69900645 -0.07674347]
fit coeffs too far off [%] [-0.86674226 -0.7060027  -0.07073414]
Trouble ahead! 3 lanes detected!
 39%|███▉      | 191/485 [00:43<01:17,  3.79it/s]
fit coeffs too far off [%] [ 1.24469331  0.84873707  0.29763414]
fit coeffs too far off [%] [ 1.28858177  0.85515893  0.29355985]
Trouble ahead! 3 lanes detected!
 40%|███▉      | 192/485 [00:43<01:23,  3.51it/s]
fit coeffs too far off [%] [-0.76365796 -0.65160458 -0.09662859]
fit coeffs too far off [%] [-0.74979998 -0.64292045 -0.10004905]
Trouble ahead! 3 lanes detected!
 40%|████      | 194/485 [00:44<01:11,  4.05it/s]
fit coeffs too far off [%] [ 0.90517095  0.63302555  0.23645815]
fit coeffs too far off [%] [-2.29604143 -1.66957403 -0.20206534]
fit coeffs too far off [%] [ 0.89210648  0.63128116  0.23906262]
fit coeffs too far off [%] [-2.52709973 -1.70200385 -0.20731586]
Trouble ahead! 3 lanes detected!
 40%|████      | 195/485 [00:44<01:37,  2.97it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-3.31719992 -2.28680788 -0.28352772]
fit coeffs too far off [%] [-3.36195681 -2.29799674 -0.28361273]
 40%|████      | 196/485 [00:45<01:37,  2.97it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.47360658  0.36303162  0.15792408]
fit coeffs too far off [%] [-3.44118179 -2.38519928 -0.29228792]
 41%|████      | 200/485 [00:45<00:49,  5.75it/s]
fit coeffs too far off [%] [-1.21312628 -1.14628211 -0.04924368]
fit coeffs too far off [%] [-1.22059794 -1.15084536 -0.04744622]
Trouble ahead! 3 lanes detected!
 42%|████▏     | 202/485 [00:46<00:54,  5.20it/s]
fit coeffs too far off [%] [ 1.70592934  1.06066804 -0.04376275]
fit coeffs too far off [%] [ 1.58467191  0.98663691 -0.04663533]
Trouble ahead! 3 lanes detected!
 42%|████▏     | 203/485 [00:46<01:06,  4.25it/s]
fit coeffs too far off [%] [ 0.56584452  0.51161834 -0.05541381]
fit coeffs too far off [%] [ 0.66638188  0.64241938 -0.07487521]
Trouble ahead! 3 lanes detected!
 42%|████▏     | 206/485 [00:47<00:53,  5.21it/s]
fit coeffs too far off [%] [-2.1845691  -2.32512843 -0.05592012]
fit coeffs too far off [%] [-2.13054372 -2.28550637 -0.04528676]
Trouble ahead! 3 lanes detected!
 43%|████▎     | 210/485 [00:47<00:44,  6.12it/s]
fit coeffs too far off [%] [-0.39974734 -1.12887349  0.2451957 ]
fit coeffs too far off [%] [-0.41679548 -1.12982633  0.22968804]
Trouble ahead! 3 lanes detected!
 45%|████▍     | 216/485 [00:48<00:36,  7.29it/s]
fit coeffs too far off [%] [ 1.16920167  0.51800581  0.00156803]
fit coeffs too far off [%] [ 1.03405641  0.46480736 -0.00188612]
Trouble ahead! 3 lanes detected!
 45%|████▍     | 218/485 [00:49<00:46,  5.74it/s]
fit coeffs too far off [%] [ 0.98421774  0.41972305  0.01769984]
fit coeffs too far off [%] [ 1.06179929  0.4889474   0.01655742]
Trouble ahead! 3 lanes detected!
 45%|████▌     | 220/485 [00:49<00:50,  5.20it/s]
fit coeffs too far off [%] [-0.8672468  -0.76822337 -0.09264202]
fit coeffs too far off [%] [-0.87863286 -0.78661988 -0.09029765]
Trouble ahead! 3 lanes detected!
 46%|████▌     | 221/485 [00:50<01:02,  4.26it/s]
fit coeffs too far off [%] [-1.67780994 -2.01224101  0.50058696]
fit coeffs too far off [%] [-1.63287979 -1.94933922  0.50908297]
Trouble ahead! 3 lanes detected!
 46%|████▌     | 223/485 [00:50<00:58,  4.45it/s]
fit coeffs too far off [%] [-0.79241105 -0.92889658  0.24578215]
fit coeffs too far off [%] [ -5.63779535 -18.68589495   0.23282536]
 46%|████▋     | 225/485 [00:50<00:44,  5.82it/s]
fit coeffs too far off [%] [-0.59813064 -0.54362956 -0.11127297]
fit coeffs too far off [%] [-1.98943349 -1.70468628 -0.19748782]
 47%|████▋     | 227/485 [00:50<00:37,  6.87it/s]
fit coeffs too far off [%] [-1.12518531 -1.3680392   0.13878101]
fit coeffs too far off [%] [ 8.47939313  3.47345925  0.10291872]
 47%|████▋     | 229/485 [00:51<00:33,  7.53it/s]
fit coeffs too far off [%] [-2.43141457 -2.11512593 -0.27172141]
fit coeffs too far off [%] [-2.54003784 -2.17855822 -0.2703971 ]
Trouble ahead! 3 lanes detected!
 48%|████▊     | 231/485 [00:51<00:44,  5.73it/s]
fit coeffs too far off [%] [-1.15496511 -0.95576961 -0.11797733]
fit coeffs too far off [%] [ -7.84226828  22.72960747   0.14463191]
 48%|████▊     | 233/485 [00:51<00:36,  6.84it/s]
fit coeffs too far off [%] [-1.07009542 -0.81391735 -0.0813721 ]
fit coeffs too far off [%] [-1.0723306  -0.80774509 -0.07699279]
Trouble ahead! 3 lanes detected!
 48%|████▊     | 235/485 [00:52<00:44,  5.59it/s]
fit coeffs too far off [%] [ 1.71823403  1.20760499  0.06863951]
fit coeffs too far off [%] [ 2.5639317   1.83820748  0.09235964]
Trouble ahead! 3 lanes detected!
 49%|████▉     | 237/485 [00:52<00:48,  5.14it/s]
fit coeffs too far off [%] [-2.64465857 -2.32979469 -0.16912106]
 49%|████▉     | 238/485 [00:52<00:42,  5.79it/s]
fit coeffs too far off [%] [-2.68430399 -2.65551394  0.31075274]
fit coeffs too far off [%] [-2.63172637 -2.57783607  0.32742754]
Trouble ahead! 3 lanes detected!
 50%|████▉     | 241/485 [00:53<00:41,  5.81it/s]
fit coeffs too far off [%] [-0.61634457 -0.55191911  0.04032251]
fit coeffs too far off [%] [ 1.22857537  0.77078818 -0.00525996]
fit coeffs too far off [%] [ 1.50738577  0.95526861 -0.00982154]
 50%|████▉     | 242/485 [00:53<00:53,  4.53it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 3.19991684  1.95482834 -0.02153246]
 51%|█████     | 245/485 [00:54<00:37,  6.46it/s]
fit coeffs too far off [%] [-0.43729465 -0.33994386 -0.17337872]
fit coeffs too far off [%] [-0.46642901 -0.60849019  0.08130115]
fit coeffs too far off [%] [-0.46754059 -0.61194131  0.08563704]
 51%|█████     | 246/485 [00:54<00:49,  4.79it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.66692658 -0.71173179  0.09599983]
fit coeffs too far off [%] [-0.70069655 -0.72079433  0.08237548]
 51%|█████     | 247/485 [00:54<00:58,  4.06it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-2.17837313 -2.75350594  0.4125409 ]
 51%|█████▏    | 249/485 [00:55<00:43,  5.49it/s]
fit coeffs too far off [%] [-2.35057292 -1.92923091 -0.32117211]
fit coeffs too far off [%] [-0.55057374 -0.71816193  0.1662002 ]
 52%|█████▏    | 251/485 [00:55<00:35,  6.62it/s]
fit coeffs too far off [%] [ 0.58040705  1.46042738 -0.10073763]
 53%|█████▎    | 256/485 [00:55<00:28,  7.95it/s]
fit coeffs too far off [%] [ 1.64020844  1.12342708 -0.00902709]
fit coeffs too far off [%] [ 1.81830358  1.14695541  0.00541045]
Trouble ahead! 3 lanes detected!
 53%|█████▎    | 257/485 [00:56<00:43,  5.30it/s]
fit coeffs too far off [%] [ 2.11907095  1.10550705  0.02146944]
fit coeffs too far off [%] [ 4.46415352  1.75205445  0.03829063]
Trouble ahead! 3 lanes detected!
 53%|█████▎    | 259/485 [00:56<00:45,  5.02it/s]
fit coeffs too far off [%] [ 5.0515866   1.83041796  0.07984473]
fit coeffs too far off [%] [-0.55294372 -0.52407611 -0.21837024]
 54%|█████▍    | 261/485 [00:57<00:35,  6.31it/s]
fit coeffs too far off [%] [-2.30676996 -2.19148771  0.06284864]
fit coeffs too far off [%] [-2.26606064 -2.56708886 -0.16528431]
 54%|█████▍    | 263/485 [00:57<00:30,  7.21it/s]
fit coeffs too far off [%] [-2.49368399 -2.38885887  0.3504129 ]
fit coeffs too far off [%] [-2.01679723 -1.97648141 -0.07125488]
 55%|█████▍    | 265/485 [00:57<00:28,  7.78it/s]
fit coeffs too far off [%] [-1.39935504 -1.50401217  0.07347703]
 55%|█████▌    | 267/485 [00:57<00:27,  8.00it/s]
fit coeffs too far off [%] [-0.90028536 -0.7711584  -0.06028401]
fit coeffs too far off [%] [-0.88820552 -0.75019562 -0.05591754]
Trouble ahead! 3 lanes detected!
 55%|█████▌    | 268/485 [00:58<00:40,  5.30it/s]
fit coeffs too far off [%] [-2.2377518  -2.16442714  0.08791608]
fit coeffs too far off [%] [-1.98806841 -2.02713118  0.09804603]
Trouble ahead! 3 lanes detected!
 56%|█████▌    | 270/485 [00:58<00:42,  5.02it/s]
fit coeffs too far off [%] [-2.22319027 -2.26730398  0.08348955]
 56%|█████▌    | 271/485 [00:58<00:37,  5.68it/s]
fit coeffs too far off [%] [ 2.79209769  1.2906406  -0.02110424]
fit coeffs too far off [%] [ 5.66782468  1.66498183  0.00702931]
Trouble ahead! 3 lanes detected!
 56%|█████▋    | 273/485 [00:59<00:41,  5.16it/s]
fit coeffs too far off [%] [ 2.00825082  0.21009213  0.12334941]
fit coeffs too far off [%] [-1.19642345 -0.84418736 -0.07570405]
 57%|█████▋    | 275/485 [00:59<00:33,  6.36it/s]
fit coeffs too far off [%] [-1.81865224  1.60458156  0.0581308 ]
 57%|█████▋    | 276/485 [00:59<00:30,  6.83it/s]
fit coeffs too far off [%] [ 2.1427161   0.7947363  -0.00505351]
fit coeffs too far off [%] [ 1.94142597  0.82401341 -0.01237235]
Trouble ahead! 3 lanes detected!
 57%|█████▋    | 277/485 [00:59<00:42,  4.91it/s]
fit coeffs too far off [%] [-1.48927878 -1.17730193 -0.61199843]
fit coeffs too far off [%] [-1.48785971 -1.17648485 -0.61371188]
Trouble ahead! 3 lanes detected!
 57%|█████▋    | 278/485 [01:00<00:50,  4.09it/s]
fit coeffs too far off [%] [-2.44425617 -1.05839289  0.01085779]
fit coeffs too far off [%] [-2.71690248 -1.06541454  0.01129048]
Trouble ahead! 3 lanes detected!
 58%|█████▊    | 280/485 [01:00<00:46,  4.39it/s]
fit coeffs too far off [%] [-4.26397828 -1.71821483  0.00764919]
fit coeffs too far off [%] [-1.686562   -1.37830063 -0.70501225]
fit coeffs too far off [%] [-0.51108079 -0.91596999 -0.00547423]
fit coeffs too far off [%] [-1.67110092 -1.3783462  -0.70301694]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ -1.28692367 -19.19910732  -0.03593216]
 58%|█████▊    | 283/485 [01:01<00:39,  5.17it/s]
fit coeffs too far off [%] [-0.55402886 -0.37739748 -0.15727566]
fit coeffs too far off [%] [ 9.91118188  1.79137441 -0.01205948]
fit coeffs too far off [%] [-1.86445827 -1.49642392 -0.73605893]
fit coeffs too far off [%] [-0.76887089 -0.47410935  0.00159057]
fit coeffs too far off [%] [-1.81283243 -1.47930769 -0.73894121]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [  6.55800627e+00   1.60987159e+00   1.66863232e-03]
 59%|█████▉    | 286/485 [01:01<00:35,  5.62it/s]
fit coeffs too far off [%] [ 0.79617974  0.52382636 -0.02957508]
fit coeffs too far off [%] [-1.21906559 -1.31045512 -0.04252218]
 59%|█████▉    | 288/485 [01:02<00:29,  6.65it/s]
fit coeffs too far off [%] [ 1.40950749  0.87952715 -0.00380989]
fit coeffs too far off [%] [-0.78363284 -0.66892515 -0.01836375]
 60%|█████▉    | 290/485 [01:02<00:26,  7.37it/s]
fit coeffs too far off [%] [ 3.84263445  2.07724893  0.01406764]
fit coeffs too far off [%] [-1.02220961 -0.91423757 -0.03843772]
 60%|██████    | 292/485 [01:02<00:25,  7.70it/s]
fit coeffs too far off [%] [-63.13059219  15.06830004   0.06352214]
fit coeffs too far off [%] [-2.40023886 -2.01931137  0.10681828]
 60%|██████    | 293/485 [01:02<00:24,  7.83it/s]
fit coeffs too far off [%] [-3.13522056 -1.8210305  -0.67917296]
fit coeffs too far off [%] [-1.87218163 -2.2383376  -0.06545995]
fit coeffs too far off [%] [-3.20169457 -1.83250671 -0.67793664]
Trouble ahead! 3 lanes detected!
 61%|██████    | 295/485 [01:03<00:32,  5.88it/s]
fit coeffs too far off [%] [-2.05310934 -1.95297727 -0.03017804]
fit coeffs too far off [%] [-3.63386517 -1.92421508 -0.6965271 ]
fit coeffs too far off [%] [-1.18981644 -1.26119732 -0.04134137]
fit coeffs too far off [%] [-3.79877802 -1.94588599 -0.69527498]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.79918494  0.42384563 -0.01495106]
 61%|██████    | 297/485 [01:03<00:35,  5.24it/s]
fit coeffs too far off [%] [ 2.57505876  1.10113408  0.32254589]
fit coeffs too far off [%] [-0.78048244 -0.7201887  -0.02268391]
fit coeffs too far off [%] [ 3.0037154   1.20530339  0.34203238]
Trouble ahead! 3 lanes detected!
 62%|██████▏   | 299/485 [01:04<00:37,  4.96it/s]
fit coeffs too far off [%] [ 1.64981854  0.911585   -0.0094753 ]
fit coeffs too far off [%] [ 1.50728703  0.56591233  0.14613437]
fit coeffs too far off [%] [-0.71722374 -0.86362846 -0.03479835]
fit coeffs too far off [%] [ 1.54399317  0.59088116  0.15731274]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.10685324  0.54847791  0.00490894]
 62%|██████▏   | 302/485 [01:04<00:33,  5.50it/s]
fit coeffs too far off [%] [-0.634753   -1.47525078 -0.01968348]
fit coeffs too far off [%] [ 7.80262647 -8.97741423  0.02161554]
 63%|██████▎   | 304/485 [01:04<00:27,  6.61it/s]
fit coeffs too far off [%] [-1.70056338 -2.0115342  -0.02275744]
fit coeffs too far off [%] [ 0.97400849  0.36187278  0.10722632]
fit coeffs too far off [%] [-3.23501026 -2.72262472  0.02864095]
fit coeffs too far off [%] [ 1.06629096  0.37061997  0.10638889]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.81032036  0.2565418   0.07152709]
fit coeffs too far off [%] [-1.04571676 -1.18513545 -0.02806294]
fit coeffs too far off [%] [ 0.87388283  0.27128984  0.07682134]
 63%|██████▎   | 305/485 [01:05<00:37,  4.84it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-11.91494191  -4.5791412    0.05459834]
 64%|██████▎   | 308/485 [01:05<00:32,  5.44it/s]
fit coeffs too far off [%] [ 1.2686813   0.96585975 -0.00160669]
fit coeffs too far off [%] [ 1.03175142  0.80422366 -0.00293499]
Trouble ahead! 3 lanes detected!
 64%|██████▎   | 309/485 [01:06<00:40,  4.35it/s]
fit coeffs too far off [%] [ 1.07674792  0.3989888   0.10610395]
fit coeffs too far off [%] [-0.67431889 -0.71074583  0.28688286]
fit coeffs too far off [%] [ 0.88541122  0.35648113  0.09879363]
Trouble ahead! 3 lanes detected!
 64%|██████▍   | 311/485 [01:06<00:38,  4.54it/s]
fit coeffs too far off [%] [-1.24207475 -1.22612006  0.00315019]
fit coeffs too far off [%] [ 2.73513393  1.12628774  0.31050562]
fit coeffs too far off [%] [ 10.36925689  17.99548601  -0.06600648]
fit coeffs too far off [%] [ 2.77663853  1.15518068  0.31731288]
Trouble ahead! 3 lanes detected!
 65%|██████▍   | 313/485 [01:07<00:36,  4.65it/s]
fit coeffs too far off [%] [ 3.16704266  1.14170256  0.27997344]
fit coeffs too far off [%] [ 0.76801928  0.55833163 -0.00927594]
fit coeffs too far off [%] [ 3.69749367  1.24746937  0.29713334]
fit coeffs too far off [%] [ 0.78740174  0.69447334 -0.01973345]
Trouble ahead! 3 lanes detected!
 65%|██████▍   | 314/485 [01:07<00:53,  3.17it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-2.22766326 -1.68289035  0.03441203]
 65%|██████▍   | 315/485 [01:07<00:43,  3.88it/s]
fit coeffs too far off [%] [ 4.32643661  1.3295448   0.31234499]
fit coeffs too far off [%] [-0.53976414 -0.88921406 -0.02566031]
fit coeffs too far off [%] [ 4.86896576  1.39741927  0.32455601]
Trouble ahead! 3 lanes detected!
 65%|██████▌   | 317/485 [01:08<00:39,  4.27it/s]
fit coeffs too far off [%] [-1.08493343 -8.63187206 -0.03497613]
fit coeffs too far off [%] [ 4.61790744  1.36031185  0.33680204]
fit coeffs too far off [%] [  2.13067738e+01   1.29770915e+00  -9.78369396e-03]
fit coeffs too far off [%] [ 4.76568874  1.38363244  0.34170783]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-1.82869741 -1.27158404  0.03662758]
 66%|██████▌   | 319/485 [01:08<00:36,  4.49it/s]
fit coeffs too far off [%] [ 5.08019332  1.41628481  0.34120665]
fit coeffs too far off [%] [-3.46216703 -6.90178172 -0.04194912]
fit coeffs too far off [%] [ 5.08870433  1.4077342   0.33695379]
Trouble ahead! 3 lanes detected!
 66%|██████▌   | 321/485 [01:09<00:35,  4.62it/s]
fit coeffs too far off [%] [ 5.79018686  1.58629249  0.3674013 ]
fit coeffs too far off [%] [ 5.91047667  1.60387801  0.3691267 ]
Trouble ahead! 3 lanes detected!
 66%|██████▋   | 322/485 [01:09<00:41,  3.97it/s]
fit coeffs too far off [%] [-0.80421639 -0.48074066 -0.01378777]
fit coeffs too far off [%] [-0.78919218 -0.46021675 -0.01254966]
Trouble ahead! 3 lanes detected!
 67%|██████▋   | 323/485 [01:09<00:44,  3.61it/s]
fit coeffs too far off [%] [ 5.70392159  1.66043714  0.38387961]
fit coeffs too far off [%] [-0.92552352 -0.55207297 -0.01553246]
fit coeffs too far off [%] [ 5.58824204  1.68415859  0.39257674]
fit coeffs too far off [%] [-0.93148079 -0.56968463 -0.01830099]
Trouble ahead! 3 lanes detected!
 67%|██████▋   | 324/485 [01:10<00:57,  2.78it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.88171238 -0.51743102 -0.01961964]
 67%|██████▋   | 325/485 [01:10<00:46,  3.47it/s]
fit coeffs too far off [%] [ 5.59739218  1.90735977  0.46288287]
fit coeffs too far off [%] [ -3.49406669e+00  -5.54510500e-01   4.85995013e-04]
fit coeffs too far off [%] [ 5.31801576  1.89616605  0.46338552]
Trouble ahead! 3 lanes detected!
 67%|██████▋   | 327/485 [01:10<00:39,  4.02it/s]
fit coeffs too far off [%] [-6.97726997  8.44793291 -0.13294328]
fit coeffs too far off [%] [-1.02571391 -0.79566324  0.14661153]
 68%|██████▊   | 329/485 [01:11<00:28,  5.43it/s]
fit coeffs too far off [%] [  1.57110596e+01  -9.74621614e-01  -5.52961696e-04]
fit coeffs too far off [%] [ -1.12515347e+00   5.45019739e+01  -1.79831149e-02]
 68%|██████▊   | 331/485 [01:11<00:23,  6.58it/s]
fit coeffs too far off [%] [ 23.93349472   3.48281602  -0.15623684]
fit coeffs too far off [%] [-1.48289143 -1.2029311   0.21786764]
 69%|██████▊   | 333/485 [01:11<00:20,  7.33it/s]
fit coeffs too far off [%] [-2.89754998 -5.72820985 -0.18909496]
 70%|██████▉   | 339/485 [01:12<00:17,  8.11it/s]
fit coeffs too far off [%] [-0.77952753 -0.97515933  0.36752392]
fit coeffs too far off [%] [-0.78098557 -0.97525845  0.37836507]
Trouble ahead! 3 lanes detected!
 70%|███████   | 341/485 [01:12<00:24,  5.98it/s]
fit coeffs too far off [%] [ 0.1802504  -0.22414684  0.18332272]
fit coeffs too far off [%] [ 0.14535542 -0.2402207   0.19300751]
Trouble ahead! 3 lanes detected!
 71%|███████   | 342/485 [01:13<00:31,  4.60it/s]
fit coeffs too far off [%] [-0.41112338 -0.40530147  0.20228084]
fit coeffs too far off [%] [-0.48612911 -0.46606305  0.2298205 ]
Trouble ahead! 3 lanes detected!
 71%|███████   | 344/485 [01:13<00:30,  4.68it/s]
fit coeffs too far off [%] [-0.49957812 -0.46865634  0.22079062]
fit coeffs too far off [%] [ 0.84915146  0.83288139 -0.18707421]
 71%|███████▏  | 346/485 [01:13<00:23,  5.95it/s]
fit coeffs too far off [%] [-1.76391413 -1.49258212  0.3655741 ]
fit coeffs too far off [%] [-1.12859637 -1.1820826   0.09263143]
 72%|███████▏  | 348/485 [01:14<00:20,  6.77it/s]
fit coeffs too far off [%] [ 0.84734695  1.17561559 -0.0453685 ]
fit coeffs too far off [%] [ 1.6111018   1.75658629 -0.04550334]
Trouble ahead! 3 lanes detected!
 72%|███████▏  | 350/485 [01:14<00:24,  5.57it/s]
fit coeffs too far off [%] [-2.01105403 -1.71022623  0.0242025 ]
fit coeffs too far off [%] [ -9.94810284 -14.28564578  -0.19934094]
 73%|███████▎  | 352/485 [01:14<00:20,  6.64it/s]
fit coeffs too far off [%] [-1.02904686 -0.97258227  0.19720517]
fit coeffs too far off [%] [-1.02934836 -0.9719265   0.18627744]
Trouble ahead! 3 lanes detected!
 73%|███████▎  | 354/485 [01:15<00:23,  5.51it/s]
fit coeffs too far off [%] [-1.23113203 -1.15024919  0.22373824]
 73%|███████▎  | 355/485 [01:15<00:21,  6.10it/s]
fit coeffs too far off [%] [ 0.9670761   1.38060352  0.04254834]
fit coeffs too far off [%] [ 0.88797329  1.2604073   0.04127008]
Trouble ahead! 3 lanes detected!
 74%|███████▎  | 357/485 [01:15<00:24,  5.31it/s]
fit coeffs too far off [%] [-8.40533364 -9.74282946 -0.21776646]
fit coeffs too far off [%] [-2.10201212 -2.54479663  0.71649457]
 74%|███████▍  | 359/485 [01:16<00:19,  6.47it/s]
fit coeffs too far off [%] [-1.61783957 -1.18453431 -0.28451095]
fit coeffs too far off [%] [-0.41849492 -0.09336161 -0.22692189]
 74%|███████▍  | 361/485 [01:16<00:17,  7.23it/s]
fit coeffs too far off [%] [ 0.66180199  1.01832384 -0.06697659]
fit coeffs too far off [%] [ 1.55801205 -0.00779827 -0.00972508]
fit coeffs too far off [%] [-0.3980556  -0.51355201  0.07084037]
fit coeffs too far off [%] [ 1.60670588 -0.00634252 -0.00959927]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 1.01909198  1.67384163 -0.11680381]
 75%|███████▍  | 363/485 [01:16<00:21,  5.73it/s]
fit coeffs too far off [%] [-2.22658594 -0.09704948 -0.0268516 ]
fit coeffs too far off [%] [-2.46806788 -0.09899245 -0.0298056 ]
Trouble ahead! 3 lanes detected!
 75%|███████▌  | 364/485 [01:17<00:27,  4.48it/s]
fit coeffs too far off [%] [-0.76323098 -0.04082738 -0.02012798]
fit coeffs too far off [%] [-0.70560711 -0.03353383 -0.01864296]
Trouble ahead! 3 lanes detected!
 75%|███████▌  | 366/485 [01:17<00:25,  4.62it/s]
fit coeffs too far off [%] [ 1.39543614 -0.01394978 -0.01709946]
 76%|███████▋  | 370/485 [01:18<00:16,  6.86it/s]
fit coeffs too far off [%] [-0.83021336 -0.99099007  0.27462311]
fit coeffs too far off [%] [-0.83002316 -0.99101663  0.27863958]
Trouble ahead! 3 lanes detected!
 76%|███████▋  | 371/485 [01:18<00:23,  4.87it/s]
fit coeffs too far off [%] [ 1.36357948 -0.05074658 -0.05113936]
fit coeffs too far off [%] [-1.34417534 -1.38568684  0.7286774 ]
fit coeffs too far off [%] [ 1.29111809 -0.03470085 -0.04323587]
fit coeffs too far off [%] [-1.33319055 -1.37919671  0.72293098]
Trouble ahead! 3 lanes detected!
 77%|███████▋  | 372/485 [01:19<00:34,  3.24it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.8305047  -0.05457358 -0.04991032]
fit coeffs too far off [%] [-1.23266696 -1.27462753  0.69789882]
 77%|███████▋  | 374/485 [01:19<00:23,  4.70it/s]
fit coeffs too far off [%] [ 0.77289848  0.00626932 -0.03277799]
 82%|████████▏ | 398/485 [01:22<00:10,  8.18it/s]
fit coeffs too far off [%] [-1.17057989 -0.63721779 -0.02589629]
fit coeffs too far off [%] [-1.16134806 -0.64937581 -0.02855068]
Trouble ahead! 3 lanes detected!
 82%|████████▏ | 399/485 [01:22<00:16,  5.36it/s]
fit coeffs too far off [%] [-1.21965946 -0.7242159  -0.03852932]
fit coeffs too far off [%] [-1.28611858 -0.68216717 -0.03286027]
Trouble ahead! 3 lanes detected!
 83%|████████▎ | 401/485 [01:22<00:16,  5.06it/s]
fit coeffs too far off [%] [-1.09841985 -0.60768699 -0.02899936]
fit coeffs too far off [%] [-4.51078481  0.82299775  0.02310678]
 83%|████████▎ | 403/485 [01:23<00:13,  6.27it/s]
fit coeffs too far off [%] [ 1.32269309  0.45126412  0.02469179]
fit coeffs too far off [%] [-1.12224605 -0.45642039 -0.01626286]
 84%|████████▎ | 405/485 [01:23<00:11,  7.11it/s]
fit coeffs too far off [%] [-4.54522992  0.41104782  0.00939872]
fit coeffs too far off [%] [-0.77841932 -0.30922226 -0.01865468]
 84%|████████▍ | 407/485 [01:23<00:10,  7.63it/s]
fit coeffs too far off [%] [-1.47538153 -0.24508408 -0.010753  ]
fit coeffs too far off [%] [ -8.69980273e+00   2.93616259e-01  -1.24844501e-03]
 84%|████████▍ | 409/485 [01:23<00:09,  7.85it/s]
fit coeffs too far off [%] [ 2.27499722  0.46430912  0.00265569]
 85%|████████▍ | 411/485 [01:24<00:09,  8.03it/s]
fit coeffs too far off [%] [ 1.88859025  1.15028695  0.05753051]
fit coeffs too far off [%] [ 1.6547192   1.01621233  0.05175528]
Trouble ahead! 3 lanes detected!
 85%|████████▍ | 412/485 [01:24<00:13,  5.31it/s]
fit coeffs too far off [%] [ 3.80984914  2.37225922  0.10480099]
fit coeffs too far off [%] [ 3.37368263  2.18216565  0.10013512]
Trouble ahead! 3 lanes detected!
 85%|████████▌ | 414/485 [01:25<00:14,  5.00it/s]
fit coeffs too far off [%] [ 3.49606639  2.34113018  0.11119628]
 87%|████████▋ | 421/485 [01:25<00:08,  7.69it/s]
fit coeffs too far off [%] [-0.47647812 -0.57557886 -0.05851525]
fit coeffs too far off [%] [-0.4250907  -0.52749401 -0.04837444]
Trouble ahead! 3 lanes detected!
 87%|████████▋ | 423/485 [01:26<00:10,  5.80it/s]
fit coeffs too far off [%] [ 0.81664178  0.71381311  0.05674774]
fit coeffs too far off [%] [ 0.79197064  0.70581436  0.0553954 ]
Trouble ahead! 3 lanes detected!
 87%|████████▋ | 424/485 [01:26<00:13,  4.49it/s]
fit coeffs too far off [%] [ 1.44394241  1.39506847  0.10682597]
fit coeffs too far off [%] [ 1.46898278  1.45140665  0.10579885]
Trouble ahead! 3 lanes detected!
 88%|████████▊ | 426/485 [01:27<00:12,  4.61it/s]
fit coeffs too far off [%] [ 0.80784517  0.67010277  0.03034031]
 88%|████████▊ | 427/485 [01:27<00:11,  5.21it/s]
fit coeffs too far off [%] [-0.80095699 -0.0648695   0.03589775]
fit coeffs too far off [%] [ 0.52631283  0.71623046  0.10760258]
fit coeffs too far off [%] [-0.77948712 -0.05468949  0.03244758]
fit coeffs too far off [%] [ 0.49735466  0.68358921  0.10601381]
Trouble ahead! 3 lanes detected!
 88%|████████▊ | 428/485 [01:27<00:17,  3.31it/s]
Trouble ahead! 3 lanes detected!
 89%|████████▊ | 430/485 [01:28<00:11,  4.77it/s]
fit coeffs too far off [%] [-0.86658148 -0.21253573 -0.07778123]
fit coeffs too far off [%] [-0.87572693 -0.23270459 -0.08647026]
Trouble ahead! 3 lanes detected!
 89%|████████▉ | 431/485 [01:28<00:13,  4.01it/s]
fit coeffs too far off [%] [ 0.74120666 -0.00795263 -0.10464665]
fit coeffs too far off [%] [ 1.05827356  0.00497551 -0.10222334]
Trouble ahead! 3 lanes detected!
 89%|████████▉ | 433/485 [01:28<00:12,  4.33it/s]
fit coeffs too far off [%] [ 1.10954164 -0.02220481 -0.12811136]
 89%|████████▉ | 434/485 [01:29<00:10,  5.03it/s]
lane too far away
fit coeffs too far off [%] [-1.12020682 -0.27925389 -0.05976742]
lane too far away
fit coeffs too far off [%] [-1.18095993 -0.21417956 -0.04185736]
Trouble ahead! 3 lanes detected!
 90%|████████▉ | 436/485 [01:29<00:10,  4.72it/s]
fit coeffs too far off [%] [ 0.96075286  0.05879572 -0.06578429]
lane too far away
fit coeffs too far off [%] [-1.02759353 -0.19636345  0.0260163 ]
lane too far away
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 1.27720293  1.23495892  0.05756652]
fit coeffs too far off [%] [ 1.24333205  1.23876545  0.05833416]
 90%|█████████ | 438/485 [01:30<00:13,  3.59it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [-0.941915   -0.26550217 -0.01723037]
fit coeffs too far off [%] [ 1.148107    1.25627377  0.0669497 ]
lane too far away
fit coeffs too far off [%] [-0.941915   -0.26550217 -0.01723037]
fit coeffs too far off [%] [ 0.95807678  1.133307    0.06986855]
Trouble ahead! 3 lanes detected!
 91%|█████████ | 439/485 [01:30<00:16,  2.76it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [ 1.12289563  1.36348375  0.09105466]
lane too far away
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 91%|█████████ | 440/485 [01:31<00:15,  2.82it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 91%|█████████ | 441/485 [01:31<00:15,  2.84it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 91%|█████████ | 442/485 [01:31<00:15,  2.86it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 91%|█████████▏| 443/485 [01:32<00:14,  2.88it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 92%|█████████▏| 444/485 [01:32<00:14,  2.88it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 92%|█████████▏| 445/485 [01:32<00:13,  2.86it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [-0.43046995 -0.57152754 -0.10009122]
lane too far away
fit coeffs too far off [%] [-0.42127036 -0.56218322 -0.09584442]
 92%|█████████▏| 446/485 [01:33<00:13,  2.86it/s]
Trouble ahead! 3 lanes detected!
 92%|█████████▏| 447/485 [01:33<00:15,  2.41it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [-0.51941907 -0.6348565  -0.09775132]
lane too far away
fit coeffs too far off [%] [-0.48498965 -0.6042707  -0.08778355]
Trouble ahead! 3 lanes detected!
 92%|█████████▏| 448/485 [01:34<00:16,  2.18it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [-0.7210856  -0.92607153 -0.13537686]
lane too far away
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [ 0.89477996  3.56503779  0.04304881]
lane too far away
 93%|█████████▎| 449/485 [01:34<00:15,  2.36it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 93%|█████████▎| 450/485 [01:34<00:13,  2.51it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 93%|█████████▎| 451/485 [01:35<00:12,  2.62it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
 93%|█████████▎| 452/485 [01:35<00:12,  2.70it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [ 0.23166612  0.64162194  0.04628847]
lane too far away
fit coeffs too far off [%] [ 0.22555921  0.68306967  0.04860573]
 93%|█████████▎| 453/485 [01:35<00:11,  2.77it/s]
Trouble ahead! 3 lanes detected!
 94%|█████████▎| 454/485 [01:36<00:13,  2.37it/s]
Trouble ahead! 3 lanes detected!
lane too far away
lane too far away
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [ 0.24927704  0.77816671  0.06019691]
lane too far away
fit coeffs too far off [%] [ 0.26859882  0.78044482  0.05735476]
 94%|█████████▍| 455/485 [01:36<00:11,  2.52it/s]
Trouble ahead! 3 lanes detected!
 94%|█████████▍| 456/485 [01:37<00:12,  2.25it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [ 0.2566447   0.80121659  0.06151489]
lane too far away
fit coeffs too far off [%] [ 0.30216452  0.8245518   0.05718991]
Trouble ahead! 3 lanes detected!
 94%|█████████▍| 457/485 [01:38<00:13,  2.08it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [ 0.58330932  1.29802657  0.0741867 ]
lane too far away
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [-0.49990617 -0.67303195 -0.07725681]
lane too far away
 94%|█████████▍| 458/485 [01:38<00:11,  2.28it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [ 0.60639074  1.15461466  0.03703046]
lane too far away
 95%|█████████▍| 460/485 [01:39<00:09,  2.54it/s]
Trouble ahead! 3 lanes detected!
lane too far away
fit coeffs too far off [%] [-0.3642585  -0.51076321 -0.0387317 ]
lane too far away
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.46496118 -0.91505253 -0.03488873]
 95%|█████████▌| 463/485 [01:39<00:05,  4.04it/s]
fit coeffs too far off [%] [-0.3438534  -3.42389524 -0.01040023]
fit coeffs too far off [%] [-0.36492558 -3.25006739 -0.0099257 ]
Trouble ahead! 3 lanes detected!
 96%|█████████▌| 465/485 [01:40<00:04,  4.36it/s]
fit coeffs too far off [%] [ 0.52374321  4.25138417  0.01606685]
fit coeffs too far off [%] [-0.30784278 -0.41652978  0.24268914]
fit coeffs too far off [%] [ 0.60973839  1.71867612  0.03887177]
fit coeffs too far off [%] [-0.30596715 -0.41604502  0.24720917]
 96%|█████████▌| 466/485 [01:40<00:05,  3.79it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-0.32960589 -0.44052526  0.2517221 ]
fit coeffs too far off [%] [-0.32670015 -0.43960697  0.25642564]
 96%|█████████▋| 467/485 [01:40<00:05,  3.51it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.45393918  0.82782971  0.04946437]
fit coeffs too far off [%] [ 0.40525335  0.76548591  0.0509924 ]
 96%|█████████▋| 468/485 [01:41<00:05,  3.33it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [ 0.33873963  0.68129191  0.0422406 ]
 97%|█████████▋| 470/485 [01:41<00:03,  4.73it/s]
fit coeffs too far off [%] [ 0.72150433  1.27168584  0.15208141]
fit coeffs too far off [%] [ 0.77817476  1.41004489  0.16026227]
Trouble ahead! 3 lanes detected!
 97%|█████████▋| 472/485 [01:41<00:02,  4.76it/s]
fit coeffs too far off [%] [-0.42314253 -0.6175802  -0.06579871]
fit coeffs too far off [%] [-0.44908427 -0.64860864 -0.07656738]
Trouble ahead! 3 lanes detected!
 98%|█████████▊| 474/485 [01:42<00:02,  4.76it/s]
fit coeffs too far off [%] [-0.65401726 -0.87333853 -0.09080127]
fit coeffs too far off [%] [-0.45391161 -1.34874408 -0.01030787]
 98%|█████████▊| 476/485 [01:42<00:01,  6.05it/s]
fit coeffs too far off [%] [-0.59304402  3.58466514 -0.02174071]
fit coeffs too far off [%] [-1.86354802 -1.19585075  0.0876588 ]
fit coeffs too far off [%] [-4.74149566  2.79740684 -0.08618962]
fit coeffs too far off [%] [-1.82743428 -1.19041483  0.09484274]
 98%|█████████▊| 477/485 [01:42<00:01,  4.64it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-2.34791917 -1.58183872  0.13873489]
fit coeffs too far off [%] [-0.87541251 -0.42467574  0.04429497]
fit coeffs too far off [%] [-2.2889501  -1.5790451   0.11237876]
 99%|█████████▊| 478/485 [01:43<00:01,  3.97it/s]
Trouble ahead! 3 lanes detected!
fit coeffs too far off [%] [-2.54556217 -1.81681348  0.17703752]
fit coeffs too far off [%] [-5.10587194 -0.40466107  0.01074004]
 99%|█████████▉| 480/485 [01:43<00:00,  5.40it/s]
fit coeffs too far off [%] [ 2.7954693  -2.0208749   0.06445518]
fit coeffs too far off [%] [ 0.42883999  1.07951707  0.02937306]
100%|██████████| 485/485 [01:44<00:00,  7.53it/s]
fit coeffs too far off [%] [ 0.21377155  0.55759457  0.03648103]

[MoviePy] Done.
[MoviePy] >>>> Video ready: ./output_images/test_results/detected_lane_challenge_video.mp4 

CPU times: user 2min 53s, sys: 4.88 s, total: 2min 58s
Wall time: 1min 44s
In [23]:
HTML("""
<video width="960" height="540" controls>
  <source src="{0}">
</video>
""".format(output2))
Out[23]:
In [ ]: